Machine Leraning Engineer

About the RoleWe 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 ResponsibilitiesDesign, 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 Skills3+ years of Machine Learning or Applied AI experienceStrong Python programming skillsHands-on experience with PyTorch or JAXDeep understanding of Transformers, LLMs, and modern deep learningExperience with RAG, embeddings, and retrieval systemsModel training, fine-tuning, evaluation, and experimentationMLOps, model serving, and production deployment experienceStrong software engineering and problem-solving abilityNice to HaveRust, C++, CUDA, or systems programmingResearch publications (NeurIPS, ICML, ICLR)Experience building developer tools or code intelligence productsDistributed training and large-scale ML infrastructureRemote? ❌ No — On-site in San Francisco.