Website:
sotalent.us
Job details:
Senior Machine Learning Engineer – MLOps
Location: Bangalore, Karnataka, India
Industry: Consumer Health / Healthcare Products
Employment Type: Full-time
Work Arrangement: Hybrid
About the Role
An established global consumer health organization is seeking a Senior Machine Learning Engineer – MLOps to design, automate, and manage the lifecycle of machine learning models.
The role focuses on building scalable, high-performance ML infrastructure on Microsoft Azure, bridging data science and production engineering. A key focus will be developing reusable, secure and cost-optimized deployment frameworks that enable ML solutions to move efficiently from development through to production.
Key Responsibilities
Pipeline Architecture & Automation
- Design and manage end-to-end ML pipelines using Azure Machine Learning, Databricks and PySpark.
- Build and maintain automated CI/CD pipelines using GitHub Actions.
- Integrate SonarQube and other automated quality and security controls.
- Develop reusable, modular templates for different ML use cases.
- Improve deployment efficiency and operational scalability across the organization.
Deployment & Orchestration
- Containerize and deploy machine learning models using Docker and Azure Kubernetes Service (AKS).
- Design and manage secure, robust APIs supporting interactions between ML models and downstream applications.
- Contribute to broader solution architecture and ensure ML components are modular and scalable.
- Support high availability and seamless scaling of production ML workloads.
Optimization & Governance
- Manage the machine learning model lifecycle from development through production.
- Monitor models for data drift and implement automated data-refresh checks.
- Optimize models and infrastructure to maintain performance and accuracy.
- Implement cost-monitoring strategies for high-compute training and deployment environments.
- Create detailed technical documentation covering workflows, pipeline templates and optimization approaches.
Collaboration
- Act as a technical liaison between Data Science, DevOps and IT teams.
- Support smooth transitions of ML solutions across development, QA and production environments.
- Collaborate with cross-functional technical stakeholders to resolve complex implementation and operational challenges.
Requirements
- Bachelor’s degree in Engineering, Computer Science or a related field.
- 5+ years of professional experience, with significant experience in Azure-based MLOps.
- Proven experience deploying and maintaining machine learning models in high-scale production environments.
- Hands-on expertise with Azure Machine Learning and Databricks.
- Strong understanding of Kubernetes / AKS or API-based deployment platforms.
- Experience with DevOps practices and Docker/containerization.
- Experience with code-quality automation tools such as SonarQube.
- Strong problem-solving and analytical capabilities.
- Ability to work effectively in a fast-paced, collaborative environment.
Preferred Qualifications
- Understanding of broader solution architecture principles.
- Azure certifications such as AI-900, DP-100 or AZ-305.
- Experience designing reusable ML deployment frameworks and scalable cloud-based ML infrastructure.
- Strong understanding of production ML governance, monitoring and cost optimization.
Click on Apply to know more.
