
Machine Learning Engineer
- India
- Permanent
- Full-time
- Scale data & training: Optimize ETL and storage workflows to handle very large datasets (up to ~25M time series).
- End-to-end workflow ownership: Manage ingestion, feature engineering, training, evaluation, deployment, and monitoring.
- Enhance parallelism & reliability: Build distributed compute solutions that minimize latency and reduce job failure rates.
- Strengthen MLOps: Develop CI/CD pipelines for models and data; ensure robust experiment tracking, observability, and reproducibility.
- Product collaboration: Work closely with design and product teams to make complex ML tasks simple within a no-/low-code environment.
- 3–6 years of product development experience in data- or ML-focused systems
- Strong computer science and software engineering fundamentals
- Expertise in:
- Data engineering and ETL pipelines
- Dataset integration and lifecycle orchestration with SQL/NoSQL stores
- CI/CD pipelines and MLOps tooling
- Programming with Python, SQL, and REST API development
- Experience with Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure)
- Exposure to Ray or other distributed-compute frameworks
- Familiarity with model monitoring, experiment tracking, and data lineage
- High ownership and collaborative mindset
- Strong systems thinking; comfortable with ambiguity
- Clear communicator who thrives in cross-functional settings
- Product-driven engineer who deeply values user experience