Senior Machine Learning Engineer

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Bengaluru 8 Years Exp Posted 201d ago

Key Responsibilities

Model Deployment & Automation
- Design and manage CI/CD pipelines for ML models using tools like MLflow, Kubeflow, or SageMaker.
- Automate model training, validation, and deployment workflows.
Infrastructure & Scalability
- Architect and maintain scalable ML infrastructure on cloud platforms (AWS, Azure, GCP).
- Optimize resource usage and model performance in production environments.
- Support distributed training and real-time inference systems.
Monitoring & Governance
- Implement monitoring systems for model drift, performance, and data integrity.
- Ensure compliance with data governance, privacy, and security standards.
- Establish observability and reliability practices for ML systems (SLOs, alerting).
Collaboration & Leadership
- Work closely with data scientists, software engineers, and DevOps teams to integrate ML solutions.
- Mentor junior ML engineers and contribute to technical leadership across projects.
Tooling & Frameworks
- Develop reusable components and libraries for ML Ops workflows.
- Evaluate and integrate new tools and technologies to improve ML lifecycle management.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
8-10 years of experience in software engineering, data science, or ML Ops.
Strong proficiency in Python, Docker, Kubernetes, and cloud-native ML tools.
Experience with ML lifecycle platforms (e.g., MLflow, TFX, Airflow).
Deep understanding of model versioning, reproducibility, and deployment strategies.