Total years of experience needed: 3+yrs

Key Responsibilities:

ML System Design & Deployment

- Build and deploy end-to-end ML pipelines (training → validation → deployment → monitoring)
- Convert notebooks and prototypes into production-grade services
- Design batch and real-time inference systems

MLOps & Infrastructure

- Implement CI/CD pipelines for ML workflows
- Work with tools like:
- MLflow / Weights & Biases
- Airflow / Prefect
- Docker / Kubernetes
- Manage model versioning, reproducibility, and experiment tracking

Data Pipeline Integration

- Collaborate with data engineering teams to:
- Build feature pipelines
- Ensure data quality and consistency
- Work with structured and unstructured data

Model Performance & Monitoring

- Set up monitoring for:
- Data drift
- Model drift
- Latency and system failures
- Define SLAs for model performance

Optimization & Scaling

- Optimize models for:
- Latency
- Cost
- Throughput
- Work on inference optimization techniques (quantization, batching, caching)

📌 Machine Learning Engineer (Bhubaneswar)
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📍 Bhubaneswar