Founding Engineer - Machine Learning

About this role

Join a Series A AI/ML startup as a Founding Engineer to architect and deploy production ML systems from scratch. You'll work closely with founders on core infrastructure, LLM integration, and distributed training pipelines while establishing technical best practices and measurable product impact.

What you'll do

• Design and optimize end-to-end ML pipelines including data ingestion, training, and deployment
• Implement and fine-tune LLMs, embeddings, and generative models for production use
• Build distributed training and inference systems on cloud infrastructure
• Develop model monitoring, evaluation, and continual learning frameworks
• Establish MLOps best practices for versioning, reproducibility, and scalability
• Collaborate with data and product teams to translate requirements into measurable ML outcomes

What they're looking for

• Python and deep learning frameworks (PyTorch, TensorFlow, or JAX)
• Distributed training and inference systems
• Cloud ML infrastructure (AWS, GCP, or Azure)
• MLOps tooling (Weights & Biases, MLflow)
• End-to-end ML pipeline development
• Feature engineering and model optimization
• Large-scale data handling and high-throughput systems
• Vector databases and RAG workflows (nice to have)

Benefits

• Salary: $220,000–$300,000 USD annually
• Early-stage equity as a founding engineer
• Work directly with founders to shape technical direction
• Build systems from scratch in a high-velocity environment
• Onsite collaboration in Mountain View, CA