
Federato

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About
Federato is an AI-driven underwriting platform that helps insurance companies optimize their risk portfolio and improve underwriting decisions. It uses deep reinforcement learning to provide real-time decision support, automate submission triage, and streamline workflows. The platform offers a single pane of glass for underwriters, an efficient submission portal for brokers, and a seamless rating interface. Federato caters to carriers, MGAs, and mutuals, helping them win more high-appetite deals faster and achieve profitable underwriting growth. The company is well-funded and has a strong leadership team with deep insurance and SaaS experience.
Platform
Features
• real-time decision support
• deep reinforcement learning
• ai-driven platform
• efficient submission portal
• automatic submission triage
• single pane of glass
• seamless rating interface
• riskops underwriting platform
Job Opportunities
Machine Learning Engineer
Federato's AI-powered platform transforms underwriting by automating submissions, providing real-time decision support, and streamlining workflows for insurance companies.
Benefits:
stock options
benefits
additional perks
Experience Requirements:
at least 6 months of relevant internship experience in a similar role
Other Requirements:
Practical experience through coursework, internships, or personal projects in applying machine learning techniques, ideally with some exposure to NLP models, prompt engineering, and working with LLMs
Familiarity with version control (Git), CI/CD pipelines, and deploying ML models or services locally or in cloud environments
Proficiency in Python for building and testing ML models, with experience using popular ML and data libraries like TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy
Enthusiasm for customer-facing work, including the ability to understand specific use cases and adjust ML models accordingly
Responsibilities:
Quickly deploy and test the current LLM-powered pipeline locally for specific customer use cases, making necessary adjustments to ensure alignment with customer requirements, and documenting findings clearly
Take ownership of deploying product improvements based on customer-specific requests, pushing code and configuration changes to GitHub, and collaborating closely with product and engineering teams for smooth integration
Build and maintain a repository of prompts for various scenarios that would be leveraged for any prospective customer proof of concept, iterating on these to optimize performance and ensure they are production-ready when needed
Lead technical PoC projects with prospective customers, showcasing the capabilities of the ML models, addressing their specific needs, and gathering feedback to inform future improvements
Collaborate with the team to ensure continuous monitoring of deployed models, focusing on improving accuracy and performance within a structured ML framework while learning best practices for pipeline maintenance
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Senior Machine Learning Engineer
Federato's AI-powered platform transforms underwriting by automating submissions, providing real-time decision support, and streamlining workflows for insurance companies.
Benefits:
stock options
benefits
additional perks
Experience Requirements:
at least 5 years
Proven experience in designing, training, benchmarking, and fine-tuning machine learning models, particularly with NLP models and large language models (LLMs)
Other Requirements:
Experience in building scalable ML pipelines using tools such as Kubeflow
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
Responsibilities:
Design and implement scalable machine learning pipelines, optimizing prompt engineering workflows to enhance accuracy and efficiency in submission intake processes across multiple insurance use cases
Evaluate and benchmark open-source large language models (LLMs), selecting and fine-tuning the most effective ones to address business-specific requirements while maintaining an eye on adaptability and future innovation
Continuously research and incorporate the latest advancements in prompt engineering and model optimization to refine prompts for precision and relevance, contributing to a robust, cutting-edge ML infrastructure
Collaborate cross-functionally, serving as a technical lead for junior team members, providing mentorship and guidance to elevate team performance and technical knowledge
Ensure production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability
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Technical Program Manager
Federato's AI-powered platform transforms underwriting by automating submissions, providing real-time decision support, and streamlining workflows for insurance companies.
Benefits:
stock options
benefits
additional perks
Education Requirements:
B.S. in Computer Science or a related technical discipline, or equivalent experience
Experience Requirements:
6+ years of software engineering, systems engineering, or technical product/program management experience
Experience owning a SaaS implementation or delivery
Other Requirements:
Knowledge of user needs, gathering requirements, and defining scope
Exceptional project management skills
Experience operating autonomously across multiple teams, demonstrated critical thinking, and thought leadership
Communication experience and previous successes in defining processes
Organizational coordination experience and experience establishing work relationships across multi-disciplinary teams and multiple partners
Analytical and problem-solving experience with complex systems and processes
Coding competence in Javascript and SQL
Responsibilities:
Lead aligned program teams to efficiently deliver successful customer implementations on time with quality
Develop and own and leverage project plans to effectively and proactively communicate program status, issues, and risks to stakeholders
Define and track key metrics and key quality and performance indicators and drive cross functional execution of program deliverables
Partner with cross functional teams to drive technical analysis, design, development, testing, implementation, and post implementation phases
Drive internal and external process improvements across multiple teams and functions including reducing the manual efforts through automation
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