Founding Machine Learning Engineer

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.

Responsibilities

• 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.

Requirements

• 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.

Pay

Base salary of $220,000 – $300,000 USD annually.

Schedule

On-site in Mountain View, California, United States.