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HomeCompaniesFlexSr. Staff Machine Learning Engineer

Sr. Staff Machine Learning Engineer

Flex · USA · Remote · Active · Greenhouse

Job facts

FieldValue
CompanyFlex
TitleSr. Staff Machine Learning Engineer
Normalized title-
Department / teamData
LocationUnited States
Work modelRemote / Remote
Employment typeFull Time (Exempt)
Salary-
Statusactive
ATS providerGreenhouse
Posted / first seen2026-06-03 / 2026-06-04
Changed / last seen2026-06-04 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Flex.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
Department jobsActive postings in Data.Open
Work model jobsActive Remote 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

CompanyFlex
Source3af7e988-7d1e-4c38-a7c5-68f4ff013b33
ATS providerGreenhouse

Description

Flex is a growth-stage, NYC headquartered FinTech company that is creating the best rent payment experience. It’s hard to believe that it’s 2026 and paying rent on time is expensive, inflexible, and difficult. We’re here to change that! Flex enables our users to pay rent throughout the month on a schedule that better fits their finances and budget. Our mission is to empower as many renters as possible with flexibility over their most significant recurring expense. After deliberately keeping a stealth profile as we built up unprecedented investor support and an enthusiastic user base, we are looking for motivated individuals to help us keep our mission growing. Will you be a part of the team? About the role We are seeking an experienced Senior Staff Machine Learning Engineer to join our dynamic team and take a leading role in developing cutting-edge machine learning systems that drive business growth. As a key technical contributor, you will drive the development, deployment, and scalability of machine learning models in a production environment, ensuring they deliver value and performance at scale. You will collaborate closely with data scientists, product teams and engineers to implement state-of-the-art solutions that power our products and services through continuous innovation. What you’ll do Own the end-to-end lifecycle of machine learning projects, from data collection and preprocessing to model deployment, monitoring, and maintenance in a production environment. Build, maintain, and optimize robust data pipelines that support model development, training, and deployment at scale. Implement machine learning algorithms and models that meet performance, scalability, and reliability requirements in a production setting. Collaborate with data scientists, engineers, and product teams to design and deploy machine learning systems that address business and product needs. Continuously monitor and improve model performance, conducting experiments, tuning hyperparameters, and ensuring models meet business objectives. Leverage distributed computing frameworks and cloud-based platforms to process large-scale datasets efficiently. Stay up-to-date with the latest advancements in machine learning, software engineering practices, and deployment strategies to keep our systems cutting-edge. Candidates with domain expertise in areas like payment risk, fraud detection, or customer success are highly preferred. Expertise and familiarity with NLP models are considered an asset. Key qualifications Master’s or Ph.D. in Computer Science, Engineering, or a related field. 6+ years of experience as a Machine Learning Engineer, with expertise in building and deploying machine learning models in production environments. Strong proficiency in Python, or similar programming languages, and experience with ML libraries like TensorFlow, PyTorch, and scikit-learn. Extensive experience with cloud platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks (e.g., Spark, Kubernetes). Proven track record of implementing end-to-end machine learning pipelines, from data preprocessing to production deployment and monitoring. Strong background in model optimization, version control, and CI/CD practices for machine learning. Excellent problem-solving abilities and the capacity to collaborate with cross-functional teams to deliver high-quality, production-ready systems. #LI-Remote Compensation Flex takes a market-based approach to pay, and compensation may vary depending on your primary work location. Work locations are categorized into one of three tiers based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be commensurate with their experience, qualifications, and Flex’s internal leveling guidelines and benchmarks. Tier 1 (NYC/Bay Area, Los Angeles, Seattle) $200,000 — $235,000 USD Tier 2 (Austin, Washington D.C. Philadelphia, San Diego, Chicago, Atlanta) $180,000 — $220,000 USD Tier 3 (Salt Lake City, all other USA cities) $170,000 — $210,000 USD Life at Flex We understand that it takes a diverse team of highly intelligent, curious, determined, empathetic, and self aware people to grow a successful company. Our HQ is located in New York City, but we have employees located throughout the US, Australia, Canada and South America. We are growing quickly, but deliberately, with a focus on building an inclusive culture. Our dynamic team has incredible perspectives to share, just as we know you do, and we take great pride in being an equal opportunity workplace. Offices Roles posted in New York, San Francisco, and Salt Lake City are hybrid positions with on-site expectations of 2-3 days per week in our local offices. For candidates outside of these areas, you may be eligible for our relocation assistance program. Benefits For full-time U.S. employees we offer: Competitive medical, dental, and vision Company equity 401(k) plan with company match Unlimited paid time off + 13 company paid holidays Parental leave Free Flex subscription For full-time non-U.S. employees, we offer: Competitive compensation + company equity Unlimited PTO

Full job record

Job ID95a99b799596c669e6e4cc076dcc1148f6fac26c
Org ID5b278cde-5cb8-4175-bb6a-219a98ee98dd
Source ID3af7e988-7d1e-4c38-a7c5-68f4ff013b33
Board ID3af7e988-7d1e-4c38-a7c5-68f4ff013b33
Providergreenhouse
Provider Job Key4699019005
TitleSr. Staff Machine Learning Engineer
Normalized Title
Statusactive
Activeyes
Location TextUSA
DepartmentData
Team
Employment Typefull-time (exempt)
Workplace Typeremote
Remote Policyremote
CountryUnited States
Region
City
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://job-boards.greenhouse.io/flex/jobs/4699019005
Apply URLhttps://job-boards.greenhouse.io/flex/jobs/4699019005
First Seen At2026-06-04 11:10:47Z
Last Seen At2026-06-06 19:58:02Z
Last Checked At2026-06-06 19:58:02Z
Last Changed At2026-06-04 11:10:47Z
Inactive At
Source Posted At2026-06-03 16:11:17Z
Source Updated At2026-06-03 16:11:17Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=flex/date=2026-06-06/2026-06-06T19-58-02-736Z-77affd72831b77cb51f6b1a55ecd8ba94a3bf33b0ce82039325f9b0da98990fe.json
Event Fields
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  "last_changed_at": "2026-06-04T11:10:47.527Z",
  "active_status": "active"
}
Parsed Structured
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    "country": "United States",
    "is_remote": true,
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  "salary_min": null,
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  "launch_scope": {
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  "workplace_type": "remote",
  "salary_currency": null
}
Extensions
{}
Native Structured
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      "location": "New York, NY",
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  "updated_at": "2026-06-03T12:11:17-04:00",
  "departments": [
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      "name": "Data",
      "child_ids": [
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  ],
  "company_name": "Flex",
  "requisition_id": 4437436005,
  "first_published": "2026-06-03T12:11:17-04:00",
  "application_deadline": null
}
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