Founding Engineer - Machine Learning

Responsibilities

• Build and optimize end-to-end ML pipelines from data ingestion through deployment.
• Implement and fine-tune LLMs, embeddings, and generative models for real-world applications.
• Develop efficient distributed training and inference systems.
• Partner with data and product teams to turn ideas into measurable ML impact.
• Contribute to model monitoring, evaluation, and continual learning frameworks.
• Establish best practices for model versioning, reproducibility, and scalability.
• Independently debug ML systems without relying on AI coding assistants.

Requirements

• 3–10 years of experience as an ML Engineer, Applied Scientist, or Research Engineer.
• Proficiency in Python and at least one of PyTorch, TensorFlow, or JAX.
• Strong understanding of data preprocessing, feature engineering, model training, and optimization.
• Hands-on experience with distributed systems, cloud ML infrastructure, and MLOps tooling such as Weights and Biases or MLflow.
• Experience working with large datasets and high-throughput systems.
• Background at an AI data, labeling, or frontier model company is a strong plus.
• Ability to work autonomously with a bias for action and enthusiasm for building from scratch.

Benefits

• Equity is included.
• On-site work in Mountain View, California, United States.