{"id":3508928,"url":"https://alion.io/job/pharmeasy-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":1107,"name":"PharmEasy","domain":"pharmeasy.in","url":"https://alion.io/company/pharmeasy","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":{"min_usd":24000,"max_usd":50000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"A/B Testing","optional":true},{"name":"Recommender Systems","optional":true}],"status":"live","first_seen_at":"2026-10-30T04:40:39Z","employer_posted_date":null,"last_verified_at":"2026-10-30T04:40:39Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Join us at PharmEasy :\n\nLaunched in 2015, PharmEasy is a consumer healthcare \"super app.\" Started with the sole purpose of making healthcare accessible and affordable to all, PharmEasy today is India's leading and most trusted online healthcare aggregator.\n\nWe provide on-demand, home-delivered access to a wide range of prescription pharmaceuticals, diagnostic test services, OTC pharmaceuticals, and other consumer healthcare products.\n\nAbout the role :\n\nYou'll work across three businesses: PharmEasy (consumer pharmacy), Ascent (B2B pharma distribution), and Thyrocare (diagnostics). This is a hands-on role where you'll build and deploy ML models yourself and own the problem areas they serve.\n\nProblems you'll work on :\n\n- Search and Recommendations\n\n- Personalization and risk modelling\n\n- Agentic AI applications\n\n- Forecasting, supply chain and inventory optimization\n\n- Pricing and margin optimization\n\n- Operations planning and routing\n\nWhat you'll do :\n\n- Build and deploy ML models end to end: data preparation, feature engineering, training, evaluation, deployment, and monitoring.\n\n- Own a problem area, from deciding what's worth building to the business metrics it moves.\n\n- Write production-quality code and work with engineering on serving, latency, and scale.\n\n- Track drift, retrain, and keep improving models after launch.\n\n- Build LLM-based agentic systems where they beat simpler approaches.\n\n- Work directly with business heads across three companies to shape what gets built.\n\nWhat you need:\n\n- 4+ years of hands-on experience building and deploying ML models.\n\n- Strong classical ML: regression, tree-based models, time-series forecasting, feature engineering, validation.\n\n- Models you've taken to production yourself, using Python, SQL, and standard MLOps tooling, with impact you can quantify.\n\n- Hands-on experience with LLM/agentic systems beyond demos.\n\n- Nice to have : Optimization or simulation, search and recommendation systems, A/B testing or causal inference, and experience in e-commerce, pharma, diagnostics, or supply chain.\n\nSkills\nMachine Learning, Monitoring Tools, LLM, Python, SQL, MLOps, Agentic AI","description_format":"text","description_chars":2147,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Medical 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