We are redirecting you to the source. If you are not redirected in 3 seconds, please click here.

Machine Learning Engineer at Weekday AI. This role is for one of the Weekday's clients. Min Experience: 4 years. JobType: full-time. We’re looking for a Machine Learning Engineer who can own ML data, training, and deployment pipelines end-to-end—making them faster, more reliable, and scalable for enterprise use. You won’t just deliver pipelines—you’ll design the architecture, optimize for performance and parallelism, and drive improvements in UX and MLOps across the ML lifecycle.. Key Responsibilities. . . 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. . . 🧠 What We’re Looking For. Must-Haves. . 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 . . . . . Nice-to-Haves. . 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 . . 🧬 Traits for Success. . 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 . . Skills:. Machine Learning | Data Engineering | MLOps | Python | SQL. Company Location: India.