Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer

Location: Pune, India

Department: Enterprise Data & Analytics Advanced Analytics Team

Employment Type: Full-time

About the Role:

We are looking for a Senior Machine Learning Engineer to join our Advanced Analytics IT Product Team. The team is responsible for developing cutting-edge data and analytics products that empower business functions to make smarter, data-driven decisions.

This role is ideal for an experienced and proactive ML engineer who enjoys solving complex problems, building scalable solutions, and working with cross-functional teams in a dynamic global environment.

Responsibilities:

• Design, build, test, deploy, and maintain machine learning and AI solutions across business domains.
• Collaborate with data scientists, engineers, and product teams to deliver reliable, production-grade ML pipelines.
• Develop data models, algorithms, and integrate them into enterprise-grade applications.
• Ensure solutions are secure, compliant, and follow industry best practices.
• Continuously improve ML products based on real-world performance metrics and feedback.
• Participate in code reviews, solution design, and incident resolution.
• Document technical designs and contribute to internal knowledge sharing.
• Lead ML engineering practices, mentor junior team members, and support agile development activities such as sprint planning and retrospectives.

Qualifications:

Education & Experience:

Master's degree in Computer Science, Machine Learning, Statistics, Physics, Mathematics, or a related field.

• 46 years of hands-on experience in machine learning, data science, or data engineering.

Technical Skills:

• Strong experience with AWS services: S3, DynamoDB, CloudFormation, CDK, Route53, AppFlow. AWS certifications are a plus.
• Hands-on experience with Databricks: PySpark, MLFlow, Unity Catalog, orchestration workflows. Databricks certifications preferred.
• Proficient in Python, SQL, and DBT.
• Familiar with tools like GitHub/GitLab, Airflow, and Terraform.
• Solid understanding of enterprise data (structured, unstructured, transactional, metadata) and integrations with systems like SAP ERP, Salesforce, and product data platforms.
• Strong foundation in CI/CD, testing practices, and production-grade software development.
• Experience with infrastructure-as-code, version control, and deployment automation.
• Knowledge of data privacy, cybersecurity, and regulatory compliance.
• Serve as the technical expert for ML engineering within the team.
• Drive architecture and design improvements for scalability and efficiency.
• Lead quality assurance activities, conduct code reviews, and ensure adherence to development standards.
• Guide and mentor junior engineers and contribute to capability building.
• Take on additional responsibilities such as Scrum Master or task force lead when needed.
• Agile working methodology with tools such as Jira, Confluence, and draw.io.
• Global, multi-cultural team focused on transparency, collaboration, and continuous learning.
• Encouraged to be self-organized, courageous, and solutions-oriented.