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Job Description
Joins us at PharmEasy:
Launched in 2015, PharmEasy is a consumer healthcare super app. Started with the sole purpose of making healthcare accessible C affordable to all, PharmEasy today is India's leading C most trusted onlinehealthcare aggregator in the country.
We provide on-demand, home-delivered access to a wide range of prescription pharmaceuticals,
diagnostic test services, OTC pharmaceuticals, C other consumer healthcare products, thereby serving your healthcare needs. Through our services, we ensure access to the best and most genuine health products, with the highest savings in the shortest time. Today, we deliver medicines in 1000+ cities in India, covering 19000+ pin codes. We offer diagnostic test services across Mumbai, Delhi, Chennai, Pune, Ahmedabad, Gandhi Nagar, Surat, Vadodara, Lucknow, Kolkata, Hyderabad, Bengaluru, and Jaipur.
About the role
You'll work across three businesses: PharmEasy (consumer pharmacy), Ascent (B2B pharma
distribution), and Thyrocare (diagnostics). This is a hands-on role. You'll build and deploy ML
models yourself and own the problem areas they serve, from deciding what to build to the
results in production. We care about shipped work with measurable impact, not papers or
leaderboard rankings.
Problems you'll work on
Search and Recommendations, Personalization, risk modelling, Agentic AI applications,
Forecasting, supply chain and inventory optimization, pricing and margin optimization,
operations planning and routing. We'll match problems to your strengths.
What you'll do
● Build and deploy ML models end to end: data preparation, feature engineering, training,
evaluation, deployment, and monitoring.
● Own a problem area, from deciding what's worth building to the business metrics it
moves.
● Write production-quality code and work with engineering on serving, latency, and scale.
● Track drift, retrain, and keep improving models after launch.
● Build LLM-based agentic systems where they beat simpler approaches.
● Work directly with business heads across three companies to shape what gets built.
What success looks like
Within your first 6 months, you'll have shipped at least one model that measurably moves a core
business metric.
What you need
● 4+ years of hands-on experience building and deploying ML models.
● Strong classical ML: regression, tree-based models, time-series forecasting, feature
engineering, validation.
● Models you've taken to production yourself, using Python, SQL, and standard MLOps
tooling, with impact you can quantify.
● Hands-on experience with LLM/agentic systems beyond demos.
● 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.
Location: Bangalore
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More Info
Key Skills
tree-based models
classical ML regression
feature engineering
time-series forecasting
ML models
LLM agentic systems
About Company
