Federato

When underwriters have real-time risk selection and portfolio insights at their fingertips, profitable growth follows!

Staff Machine Learning Engineer

Machine Learning EngineerMachine Learning EngineerFull TimeRemoteTeam 11-50H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

43 days ago

Salary

$210K - $250K / year

Bachelor Degree7 yrs expEnglishCloud

Job Description

• Design and implement scalable machine learning pipelines, serving prompt engineering workflows to enhance scalability and efficiency in submission intake processes across multiple insurance use cases. • Collaborate cross-functionally, serving as a technical lead for mid and senior 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. • Build reusable, modular infrastructure components and CI/CD pipelines for ML and LLM workloads, enabling rapid experimentation and seamless transition from research to production. • Champion best practices in observability, testing, and monitoring of ML systems, establishing standards for model/data drift detection, logging, and automated rollback strategies. • Partner with Data Science leaders to shape the vision and direction of MLOps at Federato and the future of our products

Job Requirements

  • Proven experience as a Machine Learning Engineer or similar role (at least 7 years), with a strong focus on pipelining LLM models over the last 2 years.
  • Proven experience in designing scalable and robust machine learning pipelines, both for classical machine learning and large language models (LLMs) along with familiarity with open-source models is a plus.
  • 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.
  • Experience leading a team for high-visibility / high-impact projects.
  • Proven record of influencing and executing ML product vision.

Benefits

  • Total compensation package does include stock options, benefits and additional perks.

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