Key Responsibilities :

- Design, develop, deploy, and maintain production-grade machine learning systems.

- Build and optimize scalable data pipelines for training, inference, and feature engineering.

- Develop and manage feature stores to enable efficient model development and deployment.

- Improve model performance, inference efficiency, and infrastructure cost optimization.

- Develop REST APIs for ML services using FastAPI or similar frameworks.

- Write clean, testable, and maintainable Python code with comprehensive unit and integration tests using pytest.

- Monitor production ML systems, define and maintain Service Level Objectives (SLOs), and participate in incident response and root cause analysis.

- Collaborate with Data Scientists, Data Engineers, and Product teams to translate business requirements into production-ready ML solutions.

- Own end-to-end delivery of ML projects from design through deployment and production support.

- Mentor junior engineers, conduct code reviews, and drive engineering best practices.

Required Skills :

- 6-9 years of experience in Machine Learning Engineering or Software Engineering with ML focus.

- Strong proficiency in Python, including pandas, NumPy, and scikit-learn.

- Experience building and deploying production-grade ML systems.

- Hands-on experience with feature stores and ML infrastructure.

- Strong understanding of data pipeline design and large-scale data processing.

- Experience developing APIs using FastAPI or similar frameworks.

- Expertise in model performance tuning, optimization, and cost-efficient deployment.

- Experience with testing frameworks such as pytest.

- Knowledge of monitoring, observability, SLOs, and incident management for production systems.

- Excellent problem-solving, communication, and leadership skills.

Preferred Qualifications :

- Experience with cloud platforms (AWS, Azure, or GCP).

- Familiarity with containerization and orchestration tools such as Docker and Kubernetes.

- Experience with MLOps tools and CI/CD pipelines.

- Knowledge of distributed data processing frameworks such as Spark is an advantage.