Forward Deployed Machine Learning Engineer

Federato

. Work directly on building, deploying, and iterating on machine learning models and agentic workflow features that address real customer needs .

Posted 5/1/2026full-timeRemote • 🏈 Anywhere in North AmericaJuniorMid-LevelWebsite

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

Work directly on building, deploying, and iterating on machine learning models and agentic workflow features that address real customer needs
Apply ML techniques to improve accuracy and overall system performance, ensuring solutions are robust, reliable, and production-ready for customers
Improve, implement, and validate ML models and agentic workflows supporting submission intake, underwriting decision-making, and automation tasks
Deploy and adapt autonomous agent behaviors into customer-specific workflows, translating core AI capabilities into practical solutions
Develop and maintain evaluation pipelines, monitoring systems, and performance metrics to ensure reliability under evolving production conditions
Monitor production systems via logs, metrics, and user feedback to diagnose issues, debug failures, and drive resolution
Take end-to-end ownership of problems — implementing fixes or coordinating with engineering and infrastructure teams as needed
Partner closely with Data Science and Engineering teams to iterate quickly and deliver high-impact solutions

Requirements

What you’ll need

Bachelor's or master’s degree in Mathematics, Operations Research, Data Science, Artificial Intelligence, or a related field with foundational knowledge in machine learning, deep learning, and natural language processing.
Experience working in a fast-paced, cross-functional environment
2+ years of experience as a Machine Learning Engineer, Applied Scientist, or similar role delivering ML solutions in production
Experience working directly with customers or stakeholders to translate business needs into technical solutions
Hands-on experience adapting, extending, and deploying ML/LLM systems (including agentic workflows and prompt engineering) in real-world use cases
Strong experience with experimentation, evaluation, and monitoring pipelines, including analyzing production logs and debugging systems
Experience deploying and iterating on ML systems in cloud environments in collaboration with engineering teams
Proven track record of ownership — driving issues through to resolution in production systems

Benefits

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningdeep learningnatural language processingML modelsevaluation pipelinesmonitoring systemsdebuggingprompt engineeringcloud environmentsproduction systems

Soft Skills

problem ownershipcollaborationcommunicationadaptabilitycustomer engagementcross-functional teamworkanalytical thinkingiterationstakeholder managementsolution-oriented

Certifications

Bachelor's degreeMaster's degree