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Machine Learning Engineer

March, 08

  • usaRemote
  • usaFull Time
  • usaMachine Learning
  • usaRemote
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Overview: - Federato aims to provide equitable insurance coverage leveraging AI/ML-driven platforms. - The platform optimizes risk portfolios for insurers, focusing on fair pricing in complex areas. - Federato's 'RiskOps' solution enhances underwriting decisions through data utilization. Key Responsibilities: - Deploy and test LLM-powered pipelines for customer use cases. - Own product improvements based on customer requests, integrating changes via GitHub. - Develop and maintain a repository of prompts for customer proof of concepts. - Lead technical Proof of Concept (PoC) projects with prospective customers. - Collaborate with the team for continuous monitoring and improvement of deployed models. Requirements/Skills/Qualifications: - Proven experience as a Machine Learning Engineer or similar role (minimum 6 months). - Practical ML experience, with exposure to NLP models, prompt engineering, and LLMs. - Familiarity with Git, CI/CD pipelines, and ML model deployment. - Proficiency in Python and popular ML/data libraries (TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy). - Customer-facing work experience, with adaptability to specific use cases. - Enthusiasm for learning deployment best practices and PoC tasks. Compensation & Benefits: - Salary range: $120,000 - $150,000 annually, subject to factors like location and experience. - Total compensation includes stock options, benefits, and additional perks. - Federato values culture fit, learning, and adaptability, promoting a fun and inclusive work environment. - Equal opportunity employer, providing reasonable accommodations for individuals with disabilities.
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