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Salary
≈ $24k – $50k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 5+ years exp

First seen by Alion on Oct 30, 2026.

Overview
Company
Impact
Profile match
PharmEasy is an Indian online pharmacy and healthcare platform that sells prescription and over-the-counter medicines, wellness products and diagnostic tests through its app and website. It is operated by API Holdings, which also runs diagnostic laboratories through Thyrocare and supplies retail pharmacies through a B2B distribution business. The company was founded in 2015 and is headquartered in Mumbai, Maharashtra, India.

Join us at PharmEasy :

Launched 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.

We provide on-demand, home-delivered access to a wide range of prescription pharmaceuticals, diagnostic test services, OTC pharmaceuticals, and other consumer healthcare products.

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 where you'll build and deploy ML models yourself and own the problem areas they serve.

Problems you'll work on :

- Search and Recommendations

- Personalization and risk modelling

- Agentic AI applications

- Forecasting, supply chain and inventory optimization

- Pricing and margin optimization

- Operations planning and routing

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 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.

Skills

Machine Learning, Monitoring Tools, LLM, Python, SQL, MLOps, Agentic AI

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