Founding Engineer - ML Research
About the Role
This is a founding-level ML Research Engineer opportunity at an early-stage AI/ML data and services company, working directly with the founding team to build and scale the AI research backbone from the ground up. The role sits at the intersection of applied machine learning and systems engineering, shaping research culture and pushing the boundaries of model performance and data quality in the frontier AI space.
What You'll Do
Design, train, and evaluate ML models including LLMs, diffusion models, and domain-specific architectures.
Develop scalable experimentation pipelines spanning data, model training, and evaluation workflows.
Collaborate with data and infrastructure teams to optimize training throughput and data quality.
Contribute to internal benchmarks, open research, and emerging techniques in multimodal and generative AI.
Rapidly prototype research insights and productionize them into usable tools and models.
Set foundational standards for research rigor, documentation, and reproducibility across the team.
What We're Looking For
3-10 years of experience in ML research, applied ML, or ML systems engineering.
Deep familiarity with PyTorch, JAX, or TensorFlow, and model architectures such as Transformers, Diffusion models, or RLHF.
Strong foundations in data processing, distributed training, and evaluation metrics.
Proven ability to move from research papers to working prototypes to production-ready code.
Curiosity for emerging ML paradigms - multimodality, self-learning, synthetic data, and agentic systems.
Comfort and enthusiasm for building from zero to one in a fast-moving, unstructured environment.
Compensation & Benefits
Salary: $220,000 - $300,000 USD annually. Visa sponsorship is not available for this role.
Location
On-site in Mountain View, California, United States.