Senior Machine Learning Engineer

1 week ago

Chennai, India Saaki, Argus & Averil Consulting Full time

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.

4–6 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.

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