Full-Time Senior Machine Learning Engineer

Federato is on a mission to defend the right to efficient, equitable insurance for all. We enable insurers to provide affordable coverage to people and organizations facing the issues of today – the climate crisis, cyber-attacks, social inflation, etc.

Our vision is understood and well funded by those behind Salesforce, Veeva, Zoom, Box, etc.

Federato’s AI/ML-driven platform leverages deep reinforcement learning to help insurance companies optimize the portfolio of risks they insure, allowing them to continue to provide fair and equitable pricing in difficult-to-price areas. Our category-defining ‘RiskOps’ solution drives better underwriting decisions by operationalizing underutilized data investments and surfacing real-time risk and portfolio insights.

We focus on putting insurance underwriters back in the driver’s seat, helping them meet their goals while providing an important service to society.

What You'll Be Doing

• Design and implement scalable machine learning pipelines, optimizing prompt engineering workflows to enhance accuracy and efficiency in submission intake processes across multiple insurance use cases.
• Evaluate and benchmark open-source large language models (LLMs), selecting and fine-tuning the most effective ones to address business-specific requirements while maintaining an eye on adaptability and future innovation.
• Continuously research and incorporate the latest advancements in prompt engineering and model optimization to refine prompts for precision and relevance, contributing to a robust, cutting-edge ML infrastructure.
• Collaborate cross-functionally, serving as a technical lead for junior team members, providing mentorship and guidance to elevate team performance and technical knowledge.
• Ensure production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability.

Who We Hope You Are

• Proven experience as a Machine Learning Engineer or similar role (at least 5 years), with a strong focus on pipelining LLM models over the last 3 years.
• Proven experience in designing, training, benchmarking, and fine-tuning machine learning models, particularly with NLP models and large language models (LLMs) along with familiarity with open-source models.
• Experience in building scalable ML pipelines using tools such as Kubeflow.
• Knowledge of automating and monitoring ML workflows to ensure consistent model performance in production.
• Hands-on experience with cloud platforms, including deploying models, managing cloud resources, and using relevant APIs for data intake, storage, and processing
• Great communication skills with the ability to convey complex findings to non-technical audiences.

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