Machine Leraning Engineer

About the Role

We are seeking a highly motivated Machine Learning Engineer to build production-ready AI systems that power automated code review and developer productivity. You'll work across the complete ML lifecycle—from research and data preparation to model training, evaluation, deployment, and inference optimization.

This is an ideal opportunity for engineers who enjoy combining LLMs, deep learning, software engineering, and systems thinking to solve real-world problems.

Key Responsibilities

• Design, train, and fine-tune Transformer and LLM-based models for code understanding.
• Build intelligent retrieval and RAG systems for large software repositories.
• Develop datasets, benchmarks, and evaluation frameworks to measure model quality.
• Deploy scalable ML models into production with reliable inference pipelines.
• Optimize model performance using techniques such as LoRA, distillation, and quantization.
• Collaborate with product and systems engineers to ship AI features used by developers worldwide.
• Research and implement state-of-the-art approaches in code intelligence and software engineering AI.

Must-Have Skills

• 3+ years of Machine Learning or Applied AI experience
• Strong Python programming skills
• Hands-on experience with PyTorch or JAX
• Deep understanding of Transformers, LLMs, and modern deep learning
• Experience with RAG, embeddings, and retrieval systems
• Model training, fine-tuning, evaluation, and experimentation
• MLOps, model serving, and production deployment experience
• Strong software engineering and problem-solving ability

Nice to Have

• Rust, C++, CUDA, or systems programming
• Research publications (NeurIPS, ICML, ICLR)
• Experience building developer tools or code intelligence products
• Distributed training and large-scale ML infrastructure

Remote? ❌ No — On-site in San Francisco.