Lead Machine Learning Engineer

About the Company

Pibit.ai is an SF-based insurtech company reconstructing the art and science of commercial underwriting for carriers and MGAs. Backed by Y Combinator, our proprietary CURE platform uses agentic underwriting services to automate intake, triage, and data enrichment, enabling faster underwriting and improved loss ratios.

Responsibilities

• Architect and build AI-powered product features across NLP, CV, and LLM use cases
• Own the full ML lifecycle including model training, evaluation, deployment, and monitoring
• Design and maintain scalable ML pipelines for experimentation and feature management
• Implement A/B testing frameworks and scalable inference APIs
• Optimize GPU utilization, parallel training workflows, and model fine-tuning
• Deploy LLM-based solutions tailored to specific underwriting workflows
• Implement DevOps and LLMOps best practices using Kubernetes and Docker
• Research and implement state-of-the-art techniques in Generative AI, RAG, and Transformer architectures
• Build robust data pipelines and collaborate cross-functionally to drive product decisions

Requirements

• Master’s degree in Machine Learning or a related field (or equivalent practical experience)
• 5+ years of experience in ML, software engineering, and data engineering
• Strong proficiency in Python, PyTorch, TensorFlow, and Scikit-learn
• Demonstrated experience with MLOps/LLMOps practices in production environments
• Proven ability to collaborate across research, product, and engineering teams

Preferred Qualifications

• Experience with Hugging Face, GPT, Gemini, Claude, or Llama
• Proficiency with LangChain, LangGraph, or LlamaIndex
• Experience with vector databases like Pinecone or ChromaDB
• AWS Professional Solutions Architect or AWS Machine Learning Specialty certifications
• Azure Solutions Architect Expert certification