{"id":3910744,"url":"https://alion.io/job/raydar-machine-learning-engineer-18","title":"Machine Learning Engineer","company":{"id":4478753,"name":"Raydar","domain":"raydar.com","url":"https://alion.io/company/raydar-com","size_band":"1001-5000","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":80,"open_postings":7,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":20,"computed_at":"2026-11-07T05:47:08Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":140000,"max":300000,"currency":"USD","period":"year","gross":null,"usd_annual":300000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-11-07T06:58:02Z","employer_posted_date":"2026-11-07","last_verified_at":"2026-11-07T06:58:02Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the company\nOur client is a fintech company.\nThe role\nRaydar is recruiting for this role on behalf of our client. Design, train and deploy machine learning models that make real-time risk calls in a payments setting, owning the data pipelines, evaluation and metrics behind them. The role leads modeling work as an individual contributor, with room to build and manage a team over time.\nWhat you'll do\n- Own the data pipelines and modeling design for core models, including a small language model used for contextual understanding.\n- Convert plain-language user approvals into structured, checkable limits covering vendors, amounts, items and time windows.\n- Score automated actions in real time to flag drift, substitutions, injection attempts and overspending before funds move.\n- Make risk calls from identity, user history, device and vendor signals, choosing whether to approve, request confirmation or refuse.\n- Own evaluation, labeling and metrics, tracking false approvals and false blocks as product measures.\n- Ship models into production paths with tight latency and cost budgets.\nRequirements\nWhat we're looking for\n- 2 to 5 years of experience in machine learning or related engineering work.\n- A hands-on record of training machine learning or language models, ideally including one that has operated live and driven consequential calls for users.\n- Proficiency in Python and TypeScript.\n- Sound judgment about where large language models are reliable, where they fail, and how to measure it.\n- A habit of designing evaluations before building models, and of shipping models they have built themselves.\n- Strong working knowledge in one specialty: scoring suspicious activity for fraud, building rule engines that grant or deny access, or testing and safeguarding language model outputs.\n- Comfort with a roughly six-day, in-office week (Sunday through Friday).\nBenefits\nCompensation and benefits\n- Base salary: USD 140,000 to 300,000 per year\n- Health, dental and vision coverage\nLocation and work model\n- San Francisco, California, United States\n- On-site, roughly six days a week in office (Sunday through Friday), with flexibility on weekends\n- 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