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 [email protected]
Skills Required
- Bachelor's or master's degree in Mathematics, Operations Research, Data Science, Artificial Intelligence, or related field
- 2+ years of experience as a Machine Learning Engineer, Applied Scientist, or similar role
- Experience deploying and iterating on ML systems in cloud environments
- Hands-on experience adapting, extending, and deploying ML/LLM systems
- Experience working directly with customers to translate needs into solutions
Federato Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Federato and has not been reviewed or approved by Federato.
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Fair & Transparent Compensation — Pay ranges are described as competitive for several roles, with posted bands spanning entry-level support through senior engineering and leadership. Compensation is also framed as total rewards that can include bonuses, commissions, and profit sharing in addition to base pay.
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Equity Value & Accessibility — Stock options are repeatedly referenced as part of the total compensation package, suggesting equity participation is broadly included in offers. This equity component is positioned as a meaningful add-on beyond cash compensation.
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Healthcare Strength — Health-related coverage is described as part of a standard startup benefits bundle, with references to medical, dental, and vision as included items. Benefits are characterized as solid overall even when specific plan details are not publicly enumerated.
Federato Insights
What We Do
Federato is an underwriting platform for insurance carriers that provides real-time insights to encourage empowerment, good risk taking and strong decision-making at all levels of underwriting.
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