Principal Machine Learning Engineer [T500-22539]

About FM:

FM is a 190-year-old, Fortune 500 commercial property insurance company of 6,000+ employees with a unique focus on science and risk engineering. Serving over a quarter of the Fortune 500 and major corporations globally, they deliver data-driven strategies that enhance resilience, ensure business continuity, and empower organizations to thrive.

FM India located in Bengaluru is a strategic location for driving FM's global operational efficiency that allows them to leverage the country’s talented workforce and advance their capabilities to serve their clients better.

Role Title: Senior Machine Learning Engineering Manager

Position Summary:

The Sr Data Science Solutions Manager leads a team of data scientists and machine learning engineers in the hands-on development and deployment of advanced analytics and AI solutions. Reporting to the Manager of Data Science, this role is responsible for translating strategic direction into actionable, high impact data science initiatives that drive business value. This position emphasizes technical execution, solution delivery, and team leadership while ensuring that projects are executed efficiently, models are robust and production-ready, and best practices in data science, and machine learning engineering are consistently applied. The role also includes mentoring team members, fostering a collaborative and innovative environment, and ensuring alignment with technical standards and delivery timelines. By focusing on the practical implementation of data science solutions, this role plays a critical part in operationalizing FM’s analytics capabilities and supporting the broader goals of the Analytics & AI Solutions team.

Job Responsibilities:

• Technical Leadership & Solution Delivery: Leads the hands-on development, implementation, and deployment of advanced analytics and machine learning solutions aligned with FM’s strategic direction. Ensures end-to-end ownership of data science projects, including problem framing, data preparation, model development, validation, and operationalization. Applies best practices in machine learning engineering, MLOps, and responsible AI to ensure scalable and maintainable solutions. Reviews technical work for soundness, accuracy, and alignment with business needs
• Team Management & Development: Manages a team of data scientists and ML engineers, providing mentorship, guidance, and performance evaluations. Fosters a collaborative, innovative, and inclusive team culture focused on continuous learning and technical excellence. Supports onboarding and professional development of team members to build technical depth and delivery capability.
• Project Execution & Stakeholder Collaboration: Translates strategic priorities into actionable project plans with clear milestones, timelines, and deliverables. Collaborates with cross-functional teams and business stakeholders to ensure alignment, transparency, and impact of data science solutions. Provides regular updates on project progress, risks, and outcomes to management and internal partners
• Project Execution & Stakeholder Collaboration: Translates strategic priorities into actionable project plans with clear milestones, timelines, and deliverables. Collaborates with cross-functional teams and business stakeholders to ensure alignment, transparency, and impact of data science solutions. Provides regular updates on project progress, risks, and outcomes to management and internal partners

Skill and Experience:

• 10-15 years of experience required to perform essential job functions.
• Additional Experience Qualifier (optional) : 10 years preferred. Demonstrated technical
• excellence including deep knowledge in specific disciplines. Experience with leading technical teams is preferred.
• Advanced proficiency in Python and/or R for machine learning and data science
• Hands-on experience with cloud ML platforms such as Azure ML or Databricks
• Strong knowledge of machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
• Proficiency in SQL and experience with big data tools like Spark
• Practical experience with MLOps practices including CI/CD and model monitoring
• Proven ability to lead the end-to-end development and deployment of data science solutions
• Strong understanding of software engineering practices including version control and testing
• Experience managing and mentoring technical teams
• Excellent communication skills for cross-functional collaboration and stakeholder engagement
• Ability to translate business problems into scalable, production-ready data science solution

Must Have Skills:

• Required: Machine Learning, Python & R, Databricks, Azure
• Preferred: Spark SQL, Docker, Kubernetes, ML Ops, Azure MLR, SQL

Education and Certifications:

• Graduate Degree

Work location: Bengaluru