MLOps Engineer

Designation

Consultant

Job Location

India (Remote)

Experience

2 - 4 years

• 2–4 years of hands-on experience in software/data/ML engineering in production environments
• Very strong Python - clean, production-quality code (not just notebooks); sharp problem-solving and the aptitude to pick up MLOps practices quickly
• Experience building and deploying APIs/services (FastAPI, Flask, or similar) and working knowledge of AWS (EC2, S3, Lambda) for hosting and serving
• Understanding of the end-to-end ML lifecycle - training vs inference pipelines, deployment, and monitoring
• Working knowledge of SQL and familiarity with PySpark; exposure to Databricks or comparable platforms, with the ability to read, refactor, and convert code for other environments
• CI/CD and version-control fundamentals (Git, testing, rollback); familiarity with Docker; strong ownership and comfort with a broad, evolving scope and global stakeholders
• Prior hands-on MLOps tooling experience (MLflow, model registries, drift detection, ML observability)
• Experience supporting GenAI or LLM workloads operationally (model serving, inference pipelines, cost/performance tuning)
• Master's or Bachelor's degree in Computer Science, Engineering, Math, Statistics, or a related field
• 2–4 years of relevant hands-on experience; candidates who can join immediately will be prioritized