About the Role :

We are looking for a Lead Machine Learning Engineer to design, build, and scale production-grade ML systems. This role requires a strong blend of hands-on ML expertise, software engineering, and team leadership.

Youll work on real-world problems, taking models from experimentation to deployment, while guiding a team of engineers to build robust, scalable solutions.

Key Responsibilities :

Model Development & Optimization :

- Design, train, and optimize machine learning models across use cases (NLP, recommendation systems, forecasting, etc.)

- Improve model accuracy, scalability, and efficiency

- Build and maintain reusable ML components and frameworks

Productionization & MLOps :

- Deploy ML models into production using scalable APIs and pipelines

- Build and manage end-to-end ML pipelines (data ingestion ? training ? deployment ? monitoring)

- Implement model monitoring, retraining, and performance tracking systems

- Ensure reliability, latency optimization, and cost efficiency

Engineering & Infrastructure :

- Develop backend systems using Python (FastAPI, Flask, etc.)

- Work with Docker, Kubernetes, CI/CD pipelines

- Leverage cloud platforms (AWS / GCP / Azure) for scalable ML infrastructure

Leadership & Collaboration :

- Lead and mentor a team of ML engineers and developers

- Collaborate with product, data, and engineering teams to define ML solutions

- Drive best practices in code quality, experimentation, and deployment