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.

Solid 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

📌 Senior Machine Learning Engineer (Bengaluru)
🏢 Thyrocare
📍 Bengaluru