Founding Machine Learning Engineer

Role details

ABOUT THE ROLE This is a founding-level ML engineering role at an early-stage AI data and services company, building core machine learning systems from the ground up alongside a small, high-ownership team. You'll bridge research and engineering to design, train, and ship production-grade models that directly serve frontier AI labs — and you'll help shape the technical culture and infrastructure from day one. WHAT YOU'LL DO - Build and optimize end-to-end ML pipelines, from data ingestion through to deployment. - Implement and fine-tune LLMs, embeddings, and generative models for real-world applications. - Develop efficient training and inference systems leveraging distributed compute. - Partner with data and product teams to translate ideas into measurable ML impact. - Contribute to model monitoring, evaluation, and continual learning frameworks. - Establish best practices in model versioning, reproducibility, and scalability. WHAT WE'RE LOOKING FOR - 3–10 years of experience as an ML Engineer, Applied Scientist, or Research Engineer. - Proficiency in Python and at least one major ML framework: PyTorch, TensorFlow, or JAX. - Strong grasp of ML fundamentals — data preprocessing, feature engineering, model training, and optimization. - Hands-on experience with distributed systems and cloud ML infrastructure (AWS, GCP, or Azure). - Familiarity with MLOps tooling such as Weights & Biases or MLflow. - Comfort working with large datasets and high-throughput systems. - A bias for action, ability to work autonomously, and genuine enthusiasm for building from scratch. COMPENSATION & BENEFITS Base salary of $220,000 – $300,000 USD annually. Visa sponsorship is not available for this role. LOCATION On-site in Mountain View, California, United States.