Member of Technical Staff (Research Engineering)

You'll bridge research and engineering-rapidly implementing, experimenting with, and scaling new algorithms and models. You'll work closely with scientists and founders to translate ideas into high-performance systems, and will operate across the stack from prototyping to deployment.

- Prototype and scale experimental models (LLMs, RL agents, agentic systems) on large, real-world data.

- Build tools and pipelines for training, evaluation, and analysis.

- Implement state-of-the-art research from papers and iterate in collaboration with scientists.

- Own the full ML lifecycle: data engineering, experimentation, training, and deployment.

- Operate in a highly autonomous, engineering-driven environment.

- Strong background in deep learning, reinforcement learning, or computational modeling.

- Expert-level Python and significant experience in ML frameworks (PyTorch, JAX, TensorFlow).

- Ability to translate research into robust, scalable systems.

- Experience with distributed computing or large-scale ML pipelines.

- Demonstrated curiosity and hands-on experimentation skills.