{"id":4333728,"url":"https://alion.io/job/medtronic-ai-ml-engineer","title":"AI / ML Engineer","company":{"id":4544546,"name":"Medtronic","domain":"covidien.eu","url":"https://alion.io/company/medtronic-4","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM","optional":false},{"name":"Python","optional":false},{"name":"Machine Learning","optional":true},{"name":"NLP","optional":true},{"name":"Recommender Systems","optional":true}],"status":"live","first_seen_at":"2026-11-15T09:35:31Z","employer_posted_date":null,"last_verified_at":"2026-11-15T09:35:31Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Builds the AI-powered features of OpenPHC, the worklist prioritization model, the AI Micro-Coach, and the Data Insights query layer as production features with real statistical rigor behind them, and prepares the technical evidence the Program Director needs for AI governance sign-off.\n\nResponsibilities: \nWorklist prioritization designs and builds the ranking model that determines which patients a frontline worker should follow up with first.\nAI Micro-Coach builds the content model and coaching logic for frontline worker training; the screens themselves are the Senior Full-Stack Engineer's.\nData Insights builds the natural-language query layer for administrators; the dashboard that consumes it is the Senior Full-Stack Engineer's.\nPII Masking and AI Safety: Ensures no raw PII/PHI is passed to LLM providers or external prompt logs during Micro-Coach or Data Insights processing.\nResponsible AI evidence prepares safety, appropriateness, and failure-mode documentation for each feature, feeding OpenPHC's AI governance sign-off gate.\nTest discipline builds the eval suite for each AI feature and writes automated tests against its documented requirements.\n\nDecision authority: \nDecides model architecture and implementation choices within an approved feature scope.\nNo AI feature ships without OpenPHC's sign-off on safety/privacy/cost/data-governance; this gate is prepared for by this role, never exercised by it.\n\nRequirements: \n5+ years building applied AI/ML products, with at least one shipped to real, non-technical end users.\nHands-on production experience with LLMs, prompt design, evaluation, and handling failure modes.\nStrong Python and a genuine grounding in statistics/econometrics: this role designs a ranking/prioritization model, not just an API wrapper.\nAble to scope ambiguous, not-yet-well-defined problems into something buildable.\nAI-first, 10x mindset uses AI-assisted coding and eval tooling as the default way of building and iterating on models, expected to ship production AI features at several times the pace of a traditional non-AI-assisted ML engineer without cutting corners on responsible-AI evidence.\n\nNice-to-have: \nRanking/recommendation systems experience.\nAny Indic-language NLP or speech work.\nAdaptive learning/micro-learning product experience.\nSkills\nAI, LLM, LLMs, ML, Python, Large Language Models, Machine 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