Forward Deployed Machine Learning Engineer

RemoteRemotePosted 2 days ago

Role Overview

Federato is hiring a entry-level Forward Deployed Machine Learning Engineer. This is a full-time remote role, with the team based in Remote. Part of Federato's Lifecycle hiring, posted 2 days ago. Full responsibilities, required qualifications, and the apply link are listed in the description below.

Salary Context

Salary is not disclosed in this posting. Market median for Junior-level Lifecycle roles is $77k-$102k (based on 16 comparable listings). Many employers share specifics during the interview process or after an initial screen.

Resume Keywords to Include

Make sure these keywords appear in your resume to improve ATS scoring

SalesforceORCompensationBenefitsFederatoVeevaZoomBox

Job description

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 is the only AI-native platform that spans the full policy lifecycle and changes the way insurance work gets done. Better decisioning is built-in, not bolted on: insurers' unique portfolio goals, strategies, rules, and appetite are part of the workflow so underwriters win the right deals, faster. From the moment a submission hits an underwriter’s inbox, AI is put to work, triaging submissions with a focus on high-appetite business, delivering real-time feedback on the portfolio, and consolidating workflows into a single proven system. Federato drives better business outcomes.

What You'll Be Doing:

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

Who We Hope You Are:

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

Base Salary Range: $155,000 - $180,000
Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package also includes bonus, stock options, benefits and additional perks.

Here at Federato, your capabilities are important, but culture fit is essential. We move fast, are eager to listen to our users, take a first principles approach to solving problems, and value learning and the ability to change our minds. Most importantly, we're here to have fun. Our ability to make a difference starts with our people. We would love to work with you!

We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender expression, sexual orientation, age, marital status, veteran status or disability status. We will provide reasonable accommodation to individuals with disabilities to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation at talent@federato.ai

About Federato

Federato

LifecycleHires remote

8 other open roles at Federato on TryApplyNow.

View all 9 roles at Federato

Frequently Asked Questions

How do I apply for the Forward Deployed Machine Learning Engineer position at Federato?

Use the Apply button above to submit your application directly to Federato. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.

Is the Forward Deployed Machine Learning Engineer role at Federato remote?

Yes. This is a remote role. The team is based in Remote, but the position itself does not require relocating to that office.

What does a Forward Deployed Machine Learning Engineer at Federato earn?

Federato has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.

When was the Forward Deployed Machine Learning Engineer role at Federato posted?

This role was posted on July 7, 2026 (2 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.

Is the Forward Deployed Machine Learning Engineer role at Federato entry-level?

Yes. This is an entry-level position. Strong candidates typically have 0-2 years of relevant work experience, internships, or significant project work. Read the full description for any specific qualification requirements Federato has listed.

Browse Remote Jobs Hiring Now →