ML Engineer
On-siteChennai, Tamil Nadu, India
Job Summary
Develop and maintain the core ML platform to standardize model development and deployment workflows. Create reusable MLOps components to accelerate the Data Science model lifecycle and design seamless integration of trained models with diverse production systems. Implement robust logging for real-time monitoring and establish automated systems for continuous model monitoring and performance-based retraining. Build advanced deployment strategies including Blue-Green Deployment and A/B testing frameworks, while optimizing model inference at scale using request-based scaling and flexible load distribution. Enhance CI/CD efficiency by reducing container startup times, integrating unit tests into deployment pipelines, and enabling auto deployment from GitHub. Scale and manage compute resources by implementing multi-resource configurations, troubleshooting KEDA-based scaling issues, and exploring advanced GPU architectures for cost optimization. Automate model and infrastructure configuration by loading models from cloud storage and integrating optimal open-source frameworks into the MLOps pipeline. Requires 3+ years of MLOps experience with Python, Docker, Kubernetes, and major cloud platforms.
Required Qualifications
- 3+ years of professional experience in MLOps, software engineering, and successfully deploying production-ready machine learning models
- Strong expertise in Python and advanced scripting for pipeline automation and tooling development
- Extensive hands-on experience with Docker and Kubernetes for building, managing, and debugging containerized ML environments and scalable production deployments
- Deep proficiency with MLOps frameworks (e.g., MLflow, Seldon, Kubeflow) and production-level cloud ML services (e.g., AWS SageMaker, Azure ML, GCP AI Platform)
- In-depth understanding of public cloud infrastructure and services (AWS, Azure, or GCP)
- Proven ability to evaluate, prototype, and implement open-source tools to define and guide the MLOps technology stack
- Excellent problem-solving skills and a strong analytical mindset
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