About the RoleThis 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 & BenefitsBase salary of
$220,000 - $300,000 USD annually. Visa sponsorship is not available for this role.
LocationOn-site in
Mountain View, California, United States.
