Machine Learning Engineer

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)