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Federato

Forward Deployed Machine Learning Engineer

Remote (Remote)$155k–$180kmidAdded 1 month ago

About this role

Federato seeks a Forward Deployed Machine Learning Engineer to build and deploy ML models and agentic workflows for their AI-native insurance platform. You'll work directly with customers to translate business needs into production-ready solutions, owning the full lifecycle from development through monitoring and iteration.

What you'll do

  • Build, deploy, and iterate on ML models and agentic workflow features addressing customer needs
  • Improve and validate ML models supporting submission intake, underwriting, and automation
  • Develop evaluation pipelines, monitoring systems, and performance metrics for production reliability
  • Deploy autonomous agent behaviors into customer-specific workflows
  • Monitor production systems via logs and metrics; diagnose and resolve issues
  • Partner with Data Science and Engineering teams to deliver high-impact solutions

What they're looking for

  • Machine learning and deep learning
  • Natural language processing and LLM deployment
  • Agentic workflows and prompt engineering
  • Production ML systems and cloud deployment
  • Experimentation and evaluation pipelines
  • Production monitoring and debugging
  • Customer-facing technical translation
  • Cross-functional collaboration

Benefits

  • Base salary $155,000–$180,000
  • Bonus and stock options
  • Health and benefits package
  • Remote work
  • Fast-paced, collaborative culture focused on learning
  • End-to-end ownership of impactful problems
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Federato

Federato builds an AI-native insurance platform that leverages machine learning and agentic workflows to solve customer challenges. The company is hiring technical support engineers to resolve complex customer issues and machine learning engineers to develop and deploy production ML solutions directly with customers.

View all jobs at Federato

Likely interview questions

  • Can you walk us through a machine learning model you deployed to production? What challenges did you face in moving from development to production, and how did you ensure it remained reliable?
  • Describe your experience with agentic workflows or autonomous systems. How have you adapted AI/LLM capabilities to solve specific customer problems?