About us:

We are a highly successful 190-year-old, Fortune 500 commercial property insurance company of 6,000+ employees with a unique focus on science and risk engineering. Businesses worldwide trust our expertise to protect their assets, relying on our comprehensive risk assessments and robust, engineering-based insurance solutions to safeguard against fire, natural disasters, and other perils. Serving over a quarter of the Fortune 500 and major corporations globally, we deliver data-driven strategies that enhance resilience, ensure business continuity, and empower organizations to thrive.

FM India is a strategic location for driving our global operational efficiency. Our presence in India allows us to leverage the country’s talented workforce and advance our capabilities to serve our clients better. We have diverse corporate functions that emphasize research, advanced technologies like AI and analytics, risk engineering, research, finance, marketing, HR, etc. working together to provide cutting-edge solutions and nurture lasting relationships – from co-workers to clients.

Role Title: Principal Machine Learning Engineer

Job Summary:

Principal Machine Learning Engineer with deep Databricks expertise who can architect and productionize Data Science solutions, drive ML engineering best practices, and effectively partner with MLOps teams to ensure reliable production deployment and support. This role plays a pivotal role in the Data Science team, responsible for designing, developing, and deploying advanced machine learning solutions that address complex business challenges in the property insurance domain. This role emphasizes end-to-end technical ownership of ML projects, from ideation through production, and requires close collaboration with cross-functional teams including Data Scientists,



ML Ops Engineers, and Data Engineers.

The role also contributes to mentoring junior team members to foster technical excellence and innovation.

KEY RESPONSIBILITIES:

- Expert-level Python development skills with strong software engineering practices, including code refactoring, testing, code reviews, design patterns, and performance optimization
- Proven experience productionizing Data Science solutions and transforming research notebooks and prototype code into scalable, maintainable, and production-ready ML applications.
- Deep hands-on expertise with Databricks Machine Learning capabilities, including MLflow, Model Registry, Unity Catalog, Model Serving, Batch Inference, Lake flow Jobs, MLOps Workflows, Data Profiling, and Anomaly Detection.
- Strong experience designing and implementing end-to-end machine learning workflows on Databricks, including model training, experimentation, validation, deployment, monitoring, and lifecycle management
- Experience establishing model governance and controls using Unity Catalog, including lineage tracking, access management, model lifecycle management, and compliance requirements.
- Experience working closely with MLOps teams to deploy, monitor, and support machine learning solutions in enterprise production environments
- Experience leveraging Databricks Model Serving and Batch Inference capabilities for scalable online and offline prediction workloads .

MUST HAVE SKILLS:

- Python Programming
- Databricks Machine Learning

Unity Catalog Jobs & Pipeline

MLflow

Model Registry

Model Serving

Data Profiling

Data Governance

Batch/Streaming Inference.
- SQL
- GitHub
- MLOPs Understanding
- Data Science Understanding

Education:

Minimum Education Required to Perform Essential Job Functions:

- 4 Year / bachelor's degree.

📌 Principal Machine Learning Engineer-29809] (Bengaluru)
🏢 Fm
📍 Bengaluru