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Machine Learning Engineer

Fusemachines · Kathmandu · Active · JazzHR / ApplyToJob

Job facts

FieldValue
CompanyFusemachines
TitleMachine Learning Engineer
Normalized title-
Department / team-
LocationKathmandu
Work model-
Employment typeFull Time
Salary-
Statusactive
ATS providerJazzHR / ApplyToJob
Posted / first seen2026-05-20 / 2026-05-30
Changed / last seen2026-05-30 / 2026-06-06

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PageWhat it containsOpen
Company jobsActive postings from Fusemachines.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through JazzHR / ApplyToJob.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyFusemachines
Source20a114e8-9a44-42c1-830c-a036b9148300
ATS providerJazzHR / ApplyToJob

Description

About Fusemachines Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail,  manufacturing, and government. Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI. Role Overview We're hiring Mid and Senior Data Scientists / ML Engineers to help us build the next generation of intelligent, agentic systems that solve real business problems. At this level, you'll own problems end-to-end: scoping ambiguous business questions with AI Leads, choosing the right modeling approach (classical ML, foundation models, or agentic architectures), shipping to production, and iterating based on real-world signals. Senior candidates will additionally shape technical direction, mentor others, and raise the bar for how the team uses modern AI tooling. Whether your depth is in NLP, Computer Vision, Multimodal systems, or classical ML, what we care about is your ability to reason from first principles, leverage modern AI tools to multiply your output, and turn ambiguous problems into shipped systems that move the business. Core Responsibilities Own ML projects end-to-end - from problem framing and data exploration through modeling, deployment, monitoring, and iteration.  Design and ship production ML systems spanning churn and propensity modeling, demand forecasting, anomaly detection, pricing optimization, and recommendation - using the right tool for the job, whether that's a gradient-boosted model, a fine-tuned foundation model, or an agent-based workflow. Build agentic AI workflows that automate decision-making across the business - including multi-agent systems, tool-using agents, and human-in-the-loop pipelines that combine LLM reasoning with deterministic logic and traditional ML. Leverage modern AI development tooling (AI coding assistants, agentic IDEs, automated evaluation harnesses, MLOps platforms) as a core part of your engineering practice - not an afterthought. Apply foundation models and domain-specific ML to extract signals from structured data, text, images, audio, or multimodal inputs depending on the problem at hand. Design rigorous evaluations for both deterministic models and probabilistic AI systems - offline metrics, online A/B tests, LLM-as-judge frameworks, and regression suites for non-deterministic outputs. Partner with data and platform engineers to build robust pipelines, feature stores, and serving infrastructure supporting both classical ML and modern AI workloads. Communicate effectively with technical and non-technical stakeholders - translating model behavior, tradeoffs, and risks into decisions the business can act on. (Senior) Set technical direction for an area of the ML stack, mentor mid-level and junior engineers, lead design reviews, and influence the team's tooling, evaluation standards, and architectural choices. Technical Requirements Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related quantitative field - or equivalent practical experience. 3+ years of applied data science / ML experience with a track record of shipping models to production. (Senior: 5+ years) including ownership of complex systems and demonstrable technical leadership. Strong programming proficiency in Python, including modern ML/AI libraries (PyTorch or JAX, scikit-learn, Hugging Face, pandas etc.). Solid grounding in statistical modeling, experimentation, and classical ML - regression, tree-based methods (Random Forest, XGBoost, LightGBM), time series forecasting, and anomaly detection. Hands-on experience with at least one specialty area: NLP and LLMs, Computer Vision, or Multimodal systems. We're domain-agnostic - depth in any of these is valued. Practical experience working with foundation models and LLM APIs - prompt design, structured outputs, function calling, retrieval-augmented generation (RAG), and fine-tuning where appropriate. Comfort with modern AI development workflows - using AI coding assistants and agentic IDEs (Claude Code, Cursor, Copilot, or similar) as a daily part of your engineering practice. Experience with data engineering fundamentals and big-data tooling such as PySpark, Databricks, or equivalent distributed compute frameworks. Familiarity with MLOps and LLMOps practices - version control for models and prompts, experiment tracking, CI/CD for ML, monitoring, and evaluation pipelines. (Senior) Demonstrated ability to make architectural decisions, navigate ambiguity, and influence cross-functional partners on technical strategy. Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.

Full job record

Job ID6fe56662771192c8df4abb60f6cf6c24bc42f209
Org IDbfc8b928-ce49-4e18-811c-5ee788f26e1c
Source ID20a114e8-9a44-42c1-830c-a036b9148300
Board ID20a114e8-9a44-42c1-830c-a036b9148300
Providerjazzhr
Provider Job Key9vIpSQxR3D
TitleMachine Learning Engineer
Normalized Title
Statusactive
Activeyes
Location TextKathmandu
Department
Team
Employment Typefull_time
Workplace Type
Remote Policy
CountryKathmandu
Region
City
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://jobs.fusemachines.com/apply/9vIpSQxR3D/Machine-Learning-Engineer
Apply URLhttps://jobs.fusemachines.com/apply/9vIpSQxR3D/Machine-Learning-Engineer
First Seen At2026-05-30 05:44:15Z
Last Seen At2026-06-06 19:36:53Z
Last Checked At2026-06-06 19:36:53Z
Last Changed At2026-05-30 05:44:15Z
Inactive At
Source Posted At2026-05-20 00:00:00Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=jazzhr/board=fusemachines/date=2026-06-06/2026-06-06T19-36-52-746Z-ff9e415ca692d699c5c469acd72ec95f0ace958cd632eaab39ca36e093fc2ddf.json
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    "heading": "Machine Learning Engineer",
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    "description_html": "<h3><span style=\"font-size:14px;\"><strong>About Fusemachines</strong></span></h3><p><span style=\"font-size:14px;\">Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail,  manufacturing, and government.</span></p><p><span style=\"font-size:14px;\">Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.</span></p><h2 style=\"line-height:1.38;margin-top:24px;margin-bottom:5px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Role Overview</span></span></span></span></span></span></span></h2><p style=\"line-height:1.38;margin-top:16px;margin-bottom:16px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">We're hiring Mid and Senior Data Scientists / ML Engineers to help us build the next generation of intelligent, agentic systems that solve real business problems. At this level, you'll own problems end-to-end: scoping ambiguous business questions with AI Leads, choosing the right modeling approach (classical ML, foundation models, or agentic architectures), shipping to production, and iterating based on real-world signals. Senior candidates will additionally shape technical direction, mentor others, and raise the bar for how the team uses modern AI tooling.</span></span></span></span></span></span></span></p><p style=\"line-height:1.38;margin-top:16px;margin-bottom:16px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Whether your depth is in NLP, Computer Vision, Multimodal systems, or classical ML, what we care about is your ability to reason from first principles, leverage modern AI tools to multiply your output, and turn ambiguous problems into shipped systems that move the business.</span></span></span></span></span></span></span></p><h2 style=\"line-height:1.38;margin-top:24px;margin-bottom:5px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Core Responsibilities</span></span></span></span></span></span></span></h2><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Own ML projects end-to-end</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> - from problem framing and data exploration through modeling, deployment, monitoring, and iteration. </span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Design and ship production ML systems</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> spanning churn and propensity modeling, demand forecasting, anomaly detection, pricing optimization, and recommendation - using the right tool for the job, whether that's a gradient-boosted model, a fine-tuned foundation model, or an agent-based workflow.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Build agentic AI workflows</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> that automate decision-making across the business - including multi-agent systems, tool-using agents, and human-in-the-loop pipelines that combine LLM reasoning with deterministic logic and traditional ML.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Leverage modern AI development tooling</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> (AI coding assistants, agentic IDEs, automated evaluation harnesses, MLOps platforms) as a core part of your engineering practice - not an afterthought.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Apply foundation models and domain-specific ML</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> to extract signals from structured data, text, images, audio, or multimodal inputs depending on the problem at hand.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Design rigorous evaluations</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> for both deterministic models and probabilistic AI systems - offline metrics, online A/B tests, LLM-as-judge frameworks, and regression suites for non-deterministic outputs.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Partner with data and platform engineers</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> to build robust pipelines, feature stores, and serving infrastructure supporting both classical ML and modern AI workloads.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Communicate effectively</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> with technical and non-technical stakeholders - translating model behavior, tradeoffs, and risks into decisions the business can act on.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">(Senior)</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> Set technical direction for an area of the ML stack, mentor mid-level and junior engineers, lead design reviews, and influence the team's tooling, evaluation standards, and architectural choices.</span></span></span></span></span></span></span></li></ul><h2 style=\"line-height:1.38;margin-top:24px;margin-bottom:5px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Technical Requirements</span></span></span></span></span></span></span></h2><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related quantitative field - or equivalent practical experience.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">3+ years of applied data science / ML experience with a track record of shipping models to production. (Senior: 5+ years) including ownership of complex systems and demonstrable technical leadership.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Strong programming proficiency in Python, including modern ML/AI libraries (PyTorch or JAX, scikit-learn, Hugging Face, pandas etc.).</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Solid grounding in statistical modeling, experimentation, and classical ML - regression, tree-based methods (Random Forest, XGBoost, LightGBM), time series forecasting, and anomaly detection.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Hands-on experience with at least one specialty area: NLP and LLMs, Computer Vision, or Multimodal systems. We're domain-agnostic - depth in any of these is valued.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Practical experience working with foundation models and LLM APIs - prompt design, structured outputs, function calling, retrieval-augmented generation (RAG), and fine-tuning where appropriate.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Comfort with modern AI development workflows - using AI coding assistants and agentic IDEs (Claude Code, Cursor, Copilot, or similar) as a daily part of your engineering practice.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience with data engineering fundamentals and big-data tooling such as PySpark, Databricks, or equivalent distributed compute frameworks.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Familiarity with MLOps and LLMOps practices - version control for models and prompts, experiment tracking, CI/CD for ML, monitoring, and evaluation pipelines.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">(Senior) Demonstrated ability to make architectural decisions, navigate ambiguity, and influence cross-functional partners on technical strategy.</span></span></span></span></span></span></span></li></ul><div style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><em>Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.</em></span></div>",
    "description_text": "About Fusemachines\n Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail,  manufacturing, and government.\n Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.\n Role Overview\n We're hiring Mid and Senior Data Scientists / ML Engineers to help us build the next generation of intelligent, agentic systems that solve real business problems. At this level, you'll own problems end-to-end: scoping ambiguous business questions with AI Leads, choosing the right modeling approach (classical ML, foundation models, or agentic architectures), shipping to production, and iterating based on real-world signals. Senior candidates will additionally shape technical direction, mentor others, and raise the bar for how the team uses modern AI tooling.\n Whether your depth is in NLP, Computer Vision, Multimodal systems, or classical ML, what we care about is your ability to reason from first principles, leverage modern AI tools to multiply your output, and turn ambiguous problems into shipped systems that move the business.\n Core Responsibilities\n Own ML projects end-to-end - from problem framing and data exploration through modeling, deployment, monitoring, and iteration.\n Design and ship production ML systems spanning churn and propensity modeling, demand forecasting, anomaly detection, pricing optimization, and recommendation - using the right tool for the job, whether that's a gradient-boosted model, a fine-tuned foundation model, or an agent-based workflow.\n Build agentic AI workflows that automate decision-making across the business - including multi-agent systems, tool-using agents, and human-in-the-loop pipelines that combine LLM reasoning with deterministic logic and traditional ML.\n Leverage modern AI development tooling (AI coding assistants, agentic IDEs, automated evaluation harnesses, MLOps platforms) as a core part of your engineering practice - not an afterthought.\n Apply foundation models and domain-specific ML to extract signals from structured data, text, images, audio, or multimodal inputs depending on the problem at hand.\n Design rigorous evaluations for both deterministic models and probabilistic AI systems - offline metrics, online A/B tests, LLM-as-judge frameworks, and regression suites for non-deterministic outputs.\n Partner with data and platform engineers to build robust pipelines, feature stores, and serving infrastructure supporting both classical ML and modern AI workloads.\n Communicate effectively with technical and non-technical stakeholders - translating model behavior, tradeoffs, and risks into decisions the business can act on.\n (Senior) Set technical direction for an area of the ML stack, mentor mid-level and junior engineers, lead design reviews, and influence the team's tooling, evaluation standards, and architectural choices.\n Technical Requirements\n Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related quantitative field - or equivalent practical experience.\n 3+ years of applied data science / ML experience with a track record of shipping models to production. (Senior: 5+ years) including ownership of complex systems and demonstrable technical leadership.\n Strong programming proficiency in Python, including modern ML/AI libraries (PyTorch or JAX, scikit-learn, Hugging Face, pandas etc.).\n Solid grounding in statistical modeling, experimentation, and classical ML - regression, tree-based methods (Random Forest, XGBoost, LightGBM), time series forecasting, and anomaly detection.\n Hands-on experience with at least one specialty area: NLP and LLMs, Computer Vision, or Multimodal systems. We're domain-agnostic - depth in any of these is valued.\n Practical experience working with foundation models and LLM APIs - prompt design, structured outputs, function calling, retrieval-augmented generation (RAG), and fine-tuning where appropriate.\n Comfort with modern AI development workflows - using AI coding assistants and agentic IDEs (Claude Code, Cursor, Copilot, or similar) as a daily part of your engineering practice.\n Experience with data engineering fundamentals and big-data tooling such as PySpark, Databricks, or equivalent distributed compute frameworks.\n Familiarity with MLOps and LLMOps practices - version control for models and prompts, experiment tracking, CI/CD for ML, monitoring, and evaluation pipelines.\n (Senior) Demonstrated ability to make architectural decisions, navigate ambiguity, and influence cross-functional partners on technical strategy.\n Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.",
    "jsonld_jobposting": {
      "url": "https://jobs.fusemachines.com/apply/9vIpSQxR3D/Machine-Learning-Engineer",
      "@type": "JobPosting",
      "title": "Machine Learning Engineer",
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      "datePosted": "2026-05-20",
      "description": "<h3><span style=\"font-size:14px;\"><strong>About Fusemachines</strong></span></h3><p><span style=\"font-size:14px;\">Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, the United States, Canada, and the Dominican Republic) and more than 450 full-time employees, Fusemachines brings global AI expertise to transform companies worldwide. Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail,  manufacturing, and government.</span></p><p><span style=\"font-size:14px;\">Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.</span></p><h2 style=\"line-height:1.38;margin-top:24px;margin-bottom:5px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Role Overview</span></span></span></span></span></span></span></h2><p style=\"line-height:1.38;margin-top:16px;margin-bottom:16px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">We're hiring Mid and Senior Data Scientists / ML Engineers to help us build the next generation of intelligent, agentic systems that solve real business problems. At this level, you'll own problems end-to-end: scoping ambiguous business questions with AI Leads, choosing the right modeling approach (classical ML, foundation models, or agentic architectures), shipping to production, and iterating based on real-world signals. Senior candidates will additionally shape technical direction, mentor others, and raise the bar for how the team uses modern AI tooling.</span></span></span></span></span></span></span></p><p style=\"line-height:1.38;margin-top:16px;margin-bottom:16px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Whether your depth is in NLP, Computer Vision, Multimodal systems, or classical ML, what we care about is your ability to reason from first principles, leverage modern AI tools to multiply your output, and turn ambiguous problems into shipped systems that move the business.</span></span></span></span></span></span></span></p><h2 style=\"line-height:1.38;margin-top:24px;margin-bottom:5px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Core Responsibilities</span></span></span></span></span></span></span></h2><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Own ML projects end-to-end</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> - from problem framing and data exploration through modeling, deployment, monitoring, and iteration. </span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Design and ship production ML systems</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> spanning churn and propensity modeling, demand forecasting, anomaly detection, pricing optimization, and recommendation - using the right tool for the job, whether that's a gradient-boosted model, a fine-tuned foundation model, or an agent-based workflow.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Build agentic AI workflows</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> that automate decision-making across the business - including multi-agent systems, tool-using agents, and human-in-the-loop pipelines that combine LLM reasoning with deterministic logic and traditional ML.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Leverage modern AI development tooling</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> (AI coding assistants, agentic IDEs, automated evaluation harnesses, MLOps platforms) as a core part of your engineering practice - not an afterthought.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Apply foundation models and domain-specific ML</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> to extract signals from structured data, text, images, audio, or multimodal inputs depending on the problem at hand.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Design rigorous evaluations</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> for both deterministic models and probabilistic AI systems - offline metrics, online A/B tests, LLM-as-judge frameworks, and regression suites for non-deterministic outputs.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Partner with data and platform engineers</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> to build robust pipelines, feature stores, and serving infrastructure supporting both classical ML and modern AI workloads.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Communicate effectively</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> with technical and non-technical stakeholders - translating model behavior, tradeoffs, and risks into decisions the business can act on.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">(Senior)</span></span></span><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\"> Set technical direction for an area of the ML stack, mentor mid-level and junior engineers, lead design reviews, and influence the team's tooling, evaluation standards, and architectural choices.</span></span></span></span></span></span></span></li></ul><h2 style=\"line-height:1.38;margin-top:24px;margin-bottom:5px;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:700;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Technical Requirements</span></span></span></span></span></span></span></h2><ul><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related quantitative field - or equivalent practical experience.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">3+ years of applied data science / ML experience with a track record of shipping models to production. (Senior: 5+ years) including ownership of complex systems and demonstrable technical leadership.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Strong programming proficiency in Python, including modern ML/AI libraries (PyTorch or JAX, scikit-learn, Hugging Face, pandas etc.).</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Solid grounding in statistical modeling, experimentation, and classical ML - regression, tree-based methods (Random Forest, XGBoost, LightGBM), time series forecasting, and anomaly detection.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Hands-on experience with at least one specialty area: NLP and LLMs, Computer Vision, or Multimodal systems. We're domain-agnostic - depth in any of these is valued.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Practical experience working with foundation models and LLM APIs - prompt design, structured outputs, function calling, retrieval-augmented generation (RAG), and fine-tuning where appropriate.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Comfort with modern AI development workflows - using AI coding assistants and agentic IDEs (Claude Code, Cursor, Copilot, or similar) as a daily part of your engineering practice.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Experience with data engineering fundamentals and big-data tooling such as PySpark, Databricks, or equivalent distributed compute frameworks.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">Familiarity with MLOps and LLMOps practices - version control for models and prompts, experiment tracking, CI/CD for ML, monitoring, and evaluation pipelines.</span></span></span></span></span></span></span></li><li style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><span style=\"font-variant:normal;white-space:pre-wrap;\"><span style=\"font-family:Arial, sans-serif;\"><span style=\"color:#000000;\"><span style=\"font-weight:400;\"><span style=\"font-style:normal;\"><span style=\"text-decoration:none;\">(Senior) Demonstrated ability to make architectural decisions, navigate ambiguity, and influence cross-functional partners on technical strategy.</span></span></span></span></span></span></span></li></ul><div style=\"list-style-type:disc;\"><span style=\"font-size:14px;\"><em>Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.</em></span></div>",
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