There's nothing more exciting than transforming an industry that's been stagnant for decades.
Federato is an AI-native platform that’s bringing agentic AI to the full policy lifecycle. We’re aggressively transforming how insurance work gets done, and the world is paying attention: we've raised $180 million, including a $100 million Series D from Goldman Sachs. We have powerful product-market fit, and we're growing fast globally.
You'll get to work on complex problems with one of the most advanced AI teams you'll find anywhere. If you're the person we need, you know that AI bolted onto legacy systems is too weak to matter. That's why we built our platform to be AI-native from day one. That's why you can do here what you can never do at a legacy software company. move fast and prove it, not theorize it. We think from first principles. You’ll work on problems that matter, building software that fundamentally changes how insurance operates.
What You’ll Be Doing:
- Designing and implementing efficient and scalable machine learning pipelines, across multiple insurance use cases.
- Collaborating cross-functionally, serving as a technical lead for junior team members, providing mentorship and guidance to elevate team performance and technical knowledge.
- Ensuring production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability.
- Building reusable, modular infrastructure components and CI/CD pipelines for ML and LLM workloads, enabling rapid experimentation and seamless transition from research to production.
- Championing best practices in observability, testing, and monitoring of ML systems, establishing standards for model/data drift detection, logging, and automated rollback strategies.
What We Hope You Bring:
- Proven experience as a Machine Learning Engineer or similar role (at least 8 years), with a strong focus on leveraging LLM models over the last 2 years.
- Expertise designing scalable and robust machine learning pipelines, both for classical machine learning systems and large language model applications.
- 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.
Our cash compensation amount for this role is $210,000 to $250,000 annually. 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 does include 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
- At least 8 years of experience as a Machine Learning Engineer or in a similar role
- At least 2 years of experience leveraging large language models
- Experience designing scalable and robust machine learning pipelines for classical machine learning and large language model applications
- Knowledge of automating and monitoring machine learning workflows in production
- Hands-on experience with cloud platforms, model deployment, cloud resource management, and APIs for data intake, storage, and processing
- Strong communication skills for conveying complex findings to nontechnical audiences
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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