Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer

Location: Bengaluru, Karnataka, India

Type: Full Time

Our client is seeking a Senior Machine Learning Engineer specializing in MLOps to design, deploy, and manage scalable machine learning systems. This role will focus on building robust ML infrastructure on Azure, enabling seamless deployment, monitoring, and optimization of models across the organization.

You will play a key role in bridging data science and engineering, ensuring machine learning solutions are production-ready, secure, and efficient.

Key Responsibilities

ML Pipeline Development & Automation

• Design and implement end-to-end machine learning pipelines using Azure ML, Databricks, and PySpark
• Build automated CI/CD workflows using GitHub Actions, ensuring code quality and security through integrated tools
• Develop reusable templates and frameworks to standardize ML deployments across use cases

Model Deployment & Orchestration

• Containerize and deploy ML models using Docker and Azure Kubernetes Service (AKS)
• Build and manage APIs to enable integration between ML models and business applications
• Contribute to system architecture to ensure scalable and modular ML solutions

Optimization & Governance

• Monitor model performance, detect data drift, and manage model lifecycle activities
• Implement cost optimization strategies for compute-intensive workloads
• Maintain clear, structured documentation for pipelines, workflows, and system processes

Collaboration

• Act as a key technical partner between Data Science, DevOps, and IT teams
• Support smooth transitions of models across development, testing, and production environments

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Required Qualifications

• Bachelors degree in Computer Science, Engineering, or a related field
• 5+ years of experience in machine learning engineering, with strong focus on MLOps
• Hands-on experience with Azure Machine Learning, Databricks, and cloud-based ML platforms
• Strong understanding of Kubernetes (AKS), Docker, and container-based deployments
• Experience building CI/CD pipelines and integrating code quality tools
• Proven ability to deploy and manage ML models at scale in production environments
• Strong problem-solving skills and ability to work in fast-paced, collaborative environments

Preferred Qualifications

• Knowledge of solution architecture principles for enterprise systems
• Relevant Azure certifications (e.g., AI-900, DP-100, AZ-305)
• Experience designing scalable, enterprise-grade ML frameworks