Federato
Federato is an AI-driven platform that transforms the underwriting process for insurers by providing operational efficiency and decision-making support. The platform, known as RiskOps, streamlines workflows, enhances submission triage, and offers real-time insights into account prioritization, allowing underwriters to focus on the most promising accounts. By consolidating multiple legacy systems into a unified interface, Federato helps insurance companies improve their underwriting operations and drive profitable growth.
Machine Learning Engineer
2 days ago
🇺🇸 United States – Remote
💵 $120k - $150k / year
⏰ Full Time
🟢 Junior
🤖 Machine Learning Engineer
🚫👨🎓 No degree required
Federato
Federato is an AI-driven platform that transforms the underwriting process for insurers by providing operational efficiency and decision-making support. The platform, known as RiskOps, streamlines workflows, enhances submission triage, and offers real-time insights into account prioritization, allowing underwriters to focus on the most promising accounts. By consolidating multiple legacy systems into a unified interface, Federato helps insurance companies improve their underwriting operations and drive profitable growth.
📋 Description
• Deploy and test the current LLM-powered pipeline locally for specific customer use cases• Take ownership of deploying product improvements based on customer-specific requests• Build and maintain a repository of prompts for various scenarios for customer proof of concept• Lead technical PoC projects with prospective customers, showcasing the capabilities of the ML models• Collaborate to ensure continuous monitoring of deployed models for accuracy and performance
🎯 Requirements
• Proven experience as a Machine Learning Engineer or similar role (at least 6 months of relevant internship experience in a similar role)• 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 (e.g., via frameworks like Hugging Face, OpenAI)• 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
🏖️ Benefits
• Total compensation package includes stock options, benefits, and additional perks.
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