ENGINEERING
Machine Learning Engineer
Build and ship the models behind our clients’ AI products — fine-tuned open-weight LLMs, task-specific classifiers and the serving infrastructure that carries them into production.
- San Francisco
- Engineering
- Full-time
What you’ll do
- Fine-tune and distil models against client tasks where frontier APIs fall short on cost, latency or privacy
- Build training pipelines with proper experiment tracking (MLflow, Weights & Biases)
- Deploy and monitor models in client environments, including drift detection and rollback
- Benchmark frontier and open-weight models per use case and defend the recommendation to stakeholders
- Stay current with research and fold what matters into delivery practice
What we’re looking for
- MS or PhD in Computer Science, AI, or equivalent applied experience
- Strong PyTorch skills, with experience fine-tuning transformer models (LoRA/PEFT, instruction tuning, DPO)
- Experience serving models in production with vLLM, TensorRT-LLM or managed platforms like SageMaker and Vertex AI
- Solid data engineering fundamentals for building training and eval datasets
- Judgement about when to fine-tune, when to prompt a frontier model, and when to do neither
What we offer
- Highly competitive salary
- Comprehensive health and wellness benefits
- Stock options
- Dedicated GPU and frontier-model budget
- Flexible work schedule