Lead ML Engineer

Designation - Lead ML Engineer

Experience - 7 to 14 Years

Job Location - Trivandrum or Pune

Key Responsibilities -

· Enable the successful development and deployment of Machine-Learning applications from conceptualization to production with an emphasis on operations and monitoring.

· Detect, analyze, and address bottlenecks and pain points along the ML workflow with patterns and practices that will improve quality and speed.

· Listen and engage with the product team members to ensure their adoption in a collaborative and influential fashion so that siloed behavior is prevented.

· Follow standard industry processes such as Agile, DevOps, version control, model management, deployment, and operation of ML applications.

· Keep hands-on by occasionally performing software engineering tasks such as: requirements analysis, design, development, testing, deployment, code maintenance, data pipelines, etc.

· Contribute and review architectural and other technical documentation, acting as a sparring partner.

· Mentor / train more junior colleagues in areas of expertise.

Minimum Qualifications:

· Master's degree or Ph.D. in a quantitative or engineering field like Computer Science, Physics, Mathematics, or Statistics.

· Fluency in English is a must; German is a plus.

· Previous experience in business-related functions (e.i. Sales, Operations, Claims, Underwriting, Investment Management, Asset Management, Consulting, Product Development, Finance, Market Management, Digital / Tech, etc.) is a plus.

Preferred Qualifications:

· At least 7 years of hands-on experience as part of end-to-end ML projects.

· Expertise in technical documentation practices (e.g. Arc42).

· Knowledge of continuous monitoring of the performance of ML applications and tools and environments (Grafana, Prometheus, Kubernetes, CI-CD, etc.).

· Advanced understanding of cloud technologies (AWS and Azure).

· Good understanding of the technical feasibility of data-driven products and services.

· Experience coordinating with various technical stakeholders (Engineers, Architects, Data Scientists) to achieve a common goal.

· Strong ability to self-organize, take ownership of topics, and drive them to delivery together with other team members.

· Experience in monitoring data drift in a running ML system.

· Insurance knowledge and additional languages are a plus.