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Machine Learning Engineer

Nearmap · Carlsbad, CA, United States · Hybrid · Deleted · SmartRecruiters

Job facts

FieldValue
CompanyNearmap
TitleMachine Learning Engineer
Normalized title-
Department / teamEngineering & Technology
LocationCarlsbad, CA, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary-
Statusdeleted
ATS providerSmartRecruiters
Posted / first seen2026-05-10 / 2026-05-31
Changed / last seen2026-06-06 / 2026-06-03

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PageWhat it containsOpen
Company jobsActive postings from Nearmap.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through SmartRecruiters.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Carlsbad.Open
Department jobsActive postings in Engineering & Technology.Open
Work model jobsActive Hybrid postings.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

CompanyNearmap
Source85198f3f-3d44-4027-a63a-b02d5410ba34
ATS providerSmartRecruiters

Description

Property intelligence is reshaping how the world understands the built environment, and Nearmap is driving that. We put powerful aerial imagery, AI-driven analytics, and geospatial tools into the hands of the people who plan, build, insure, and govern the places we all live and work. Our technology turns property uncertainty into decisive action, and our culture brings out the best in the people who build it. About the Role We're looking for a Machine Learning Engineer to join our Insurance AI team. You'll be the engineering backbone for our Data Scientists, building and maintaining the ML infrastructure that turns models into reliable, scalable products. This isn't a greenfield build-everything-from-scratch role. Our Sydney-based AI & Computer Vision team has built robust ML tooling and pipelines. Your job is to extend, adapt, and maintain that infrastructure for US-specific use cases. If you're someone who gets satisfaction from making existing systems work better rather than reinventing the wheel, keep reading. You'll work closely with Data Scientists in the US and ML Engineers in Australia, acting as the technical bridge that keeps both teams moving fast. What You'll Do You'll own the ML engineering function for the US Insurance AI team. That means building data and model pipelines, integrating with internal and external APIs, and making sure our Data Scientists have the tools they need to ship models to production. You'll collaborate daily with our Sydney AICV team to leverage shared infrastructure and contribute improvements back. Day to day, you'll write Python, wrangle data pipelines, debug production issues, and translate Data Scientist requirements into working systems. You'll use AWS, work with cloud-native technologies, and operate within an established MLOps framework. Key Responsibilities Build and maintain ML pipelines for data ingestion, feature processing, model training, deployment, and monitoring in AWS Extend and adapt existing tooling from our Sydney AICV team for US Insurance AI use cases Develop and support internal tools and frameworks that streamline experimentation and improve delivery speed Integrate internal and external APIs to connect datasets, models, and services Partner with Data Scientists to understand their workflow needs and translate them into scalable technical solutions Ensure infrastructure supports rapid experimentation while maintaining reliability, security, and scalability Collaborate with Technical Product Managers, API engineers, and platform teams to deploy models in production Contribute to a shared codebase through feature branches, pull requests, and code reviews You'll need: 2-4 years as a Machine Learning Engineer or ML-focused Software Engineer Strong Python skills with a track record of writing clean, tested, production-grade code Hands-on experience with ML libraries like PyTorch, scikit-learn, and pandas Experience building and maintaining ML pipelines in production environments Solid SQL skills and familiarity with data engineering tools (Airflow, Spark, or dbt) The ability to jump into an existing codebase, understand it, and extend it Clear communication skills and comfort working across time zones It would be great if you also have: AWS experience (S3, EC2, ECS, or similar) Experience consuming and integrating REST APIs at scale Docker and containerisation experience MLOps experience including CI/CD and model monitoring Familiarity with geospatial or aerial imagery data Experience with pipeline orchestration tools like Ray, Kubeflow, or Flyte Who You Are You're mid-career and self-sufficient. You don't need someone looking over your shoulder, but you also know when to ask questions. You'd rather build on a solid foundation than start from scratch just to put your stamp on something. You communicate clearly, collaborate well with remote teams, and care about shipping things that actually work. To help us get to know the real you: In your application, tell us about a specific ML pipeline you've built or maintained and one thing you learned from it. Skip the AI-generated cover letters. We want to hear your voice. Why you'll love working at Nearmap: We move fast and work smart; often wearing multiple hats. We adapted to remote working with ease and are continually looking at ways to improve. We’re proud of our inclusive, supportive culture, and maintain a safe environment where everyone feels a sense of belonging and can be themselves. In addition to your annual leave, Nearmap offers: 4 extra "YOU" days off each year—take a break, no questions asked! Company-sponsored volunteering days to give back. Generous parental leave policies for growing families. Work from Overseas Policy - explore the world in the approved list of cities while you work! Access to LinkedIn Learning for continuous growth. Discounted Private Health Insurance plans. Monthly wellbeing and technology allowance. A Nearmap subscription (naturally!). Learn More About The Work We Do YouTube Page LinkedIn Page Thanks, but we got this! Nearmap does not accept unsolicited resumes from recruitment agencies and search firms. Please do not email or send unsolicited resumes to any Nearmap employee, location or address. Nearmap is not responsible for any fees related to unsolicited resumes.

Full job record

Job ID3d58c3ce9f5b4f486efaa7797331d9b1eba283d1
Org ID6326085e-0a16-4c8d-b29b-a4de56d79342
Source ID85198f3f-3d44-4027-a63a-b02d5410ba34
Board ID85198f3f-3d44-4027-a63a-b02d5410ba34
Providersmartrecruiters
Provider Job Key744000125617209
TitleMachine Learning Engineer
Normalized Title
Statusdeleted
Activeno
Location TextCarlsbad, CA, United States
DepartmentEngineering & Technology
Team
Employment Typefull_time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CityCarlsbad
Salary RawProperty intelligence is reshaping how the world understands the built environment, and Nearmap is driving that. We put powerful aerial imagery, AI-driven analytics, and geospatial tools into the hands of the people who plan, build, insure, and govern the places we all live and work. Our technology turns property uncertainty into decisive action, and our culture brings out the best in the people who build it. About the Role We're looking for a Machine Learning Engineer to join our Insurance AI team. You'll be the engineering backbone for our Data Scientists, building and maintaining the ML infrastructure that turns models into reliable, scalable products. This isn't a greenfield build-everything-from-scratch role. Our Sydney-based AI & Computer Vision team has built robust ML tooling and pipelines. Your job is to extend, adapt, and maintain that infrastructure for US-specific use cases. If you're someone who gets satisfaction from making existing systems work better rather than reinventing the wheel, keep reading. You'll work closely with Data Scientists in the US and ML Engineers in Australia, acting as the technical bridge that keeps both teams moving fast. What You'll Do You'll own the ML engineering function for the US Insurance AI team. That means building data and model pipelines, integrating with internal and external APIs, and making sure our Data Scientists have the tools they need to ship models to production. You'll collaborate daily with our Sydney AICV team to leverage shared infrastructure and contribute improvements back. Day to day, you'll write Python, wrangle data pipelines, debug production issues, and translate Data Scientist requirements into working systems. You'll use AWS, work with cloud-native technologies, and operate within an established MLOps framework. Key Responsibilities Build and maintain ML pipelines for data ingestion, feature processing, model training, deployment, and monitoring in AWS Extend and adapt existing tooling from our Sydney AICV team for US Insurance AI use cases Develop and support internal tools and frameworks that streamline experimentation and improve delivery speed Integrate internal and external APIs to connect datasets, models, and services Partner with Data Scientists to understand their workflow needs and translate them into scalable technical solutions Ensure infrastructure supports rapid experimentation while maintaining reliability, security, and scalability Collaborate with Technical Product Managers, API engineers, and platform teams to deploy models in production Contribute to a shared codebase through feature branches, pull requests, and code reviews You'll need: 2-4 years as a Machine Learning Engineer or ML-focused Software Engineer Strong Python skills with a track record of writing clean, tested, production-grade code Hands-on experience with ML libraries like PyTorch, scikit-learn, and pandas Experience building and maintaining ML pipelines in production environments Solid SQL skills and familiarity with data engineering tools (Airflow, Spark, or dbt) The ability to jump into an existing codebase, understand it, and extend it Clear communication skills and comfort working across time zones It would be great if you also have: AWS experience (S3, EC2, ECS, or similar) Experience consuming and integrating REST APIs at scale Docker and containerisation experience MLOps experience including CI/CD and model monitoring Familiarity with geospatial or aerial imagery data Experience with pipeline orchestration tools like Ray, Kubeflow, or Flyte Who You Are You're mid-career and self-sufficient. You don't need someone looking over your shoulder, but you also know when to ask questions. You'd rather build on a solid foundation than start from scratch just to put your stamp on something. You communicate clearly, collaborate well with remote teams, and care about shipping things that actually work. To help us get to know the real you: In your application, tell us about a specific ML pipeline you've built or maintained and one thing you learned from it. Skip the AI-generated cover letters. We want to hear your voice. Why you'll love working at Nearmap: We move fast and work smart; often wearing multiple hats. We adapted to remote working with ease and are continually looking at ways to improve. We’re proud of our inclusive, supportive culture, and maintain a safe environment where everyone feels a sense of belonging and can be themselves. In addition to your annual leave, Nearmap offers: 4 extra "YOU" days off each year—take a break, no questions asked! Company-sponsored volunteering days to give back. Generous parental leave policies for growing families. Work from Overseas Policy - explore the world in the approved list of cities while you work! Access to LinkedIn Learning for continuous growth. Discounted Private Health Insurance plans. Monthly wellbeing and technology allowance. A Nearmap subscription (naturally!). Learn More About The Work We Do YouTube Page LinkedIn Page Thanks, but we got this! Nearmap does not accept unsolicited resumes from recruitment agencies and search firms. Please do not email or send unsolicited resumes to any Nearmap employee, location or address. Nearmap is not responsible for any fees related to unsolicited resumes.
Salary Min
Salary Max
Salary Currency
Salary Periodday
Source URLhttps://jobs.smartrecruiters.com/Nearmap/744000125617209-machine-learning-engineer
Apply URLhttps://jobs.smartrecruiters.com/Nearmap/744000125617209-machine-learning-engineer?oga=true
First Seen At2026-05-31 17:42:19Z
Last Seen At2026-06-03 11:08:17Z
Last Checked At2026-06-06 10:49:48Z
Last Changed At2026-06-06 10:49:48Z
Inactive At2026-06-06 10:49:48Z
Source Posted At2026-05-10 23:03:18Z
Source Updated At
Raw Payload Uris3://bluework-jobs-prod-raw-590183727216/raw/provider=smartrecruiters/board=nearmap/date=2026-06-03/2026-06-03T11-08-15-774Z-658f67dbee252031cc8894e58a6a829acf9603c18904ba75ac336fbfb440c152.json
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