Member of Technical Staff - Machine Learning Capabilities, New Graduates

About the role

We are looking for new Graduate Machine Learning Engineers to design and build reinforcement learning environments to safely advance model capabilities in machine learning research and engineering.

Responsibilities

• Design and build RL environments and reward schemes that produce clean, learnable signals for frontier models on ML research and engineering tasks.
• Build deep expertise across the frontier of ML research, training, and inference infrastructure.
• Collaborate with others to brainstorm and create new ideas and tools to improve the environment building process.

Requirements

• You have strong ML fundamentals and broad research interests.
• You read many papers or tutorials, understand topics deeply and have the creativity to translate them into RLVR problems.
• Proficiency in Python and systems programming; ideally PyTorch or JAX.
• Smart problem solvers who take ownership and drive solutions end-to-end.
• Passion for staying current with the rapidly evolving ML infrastructure landscape.
• Able to meet throughput expectations and respond quickly to feedback.

Qualifications

• You have strong ML fundamentals and broad research interests.
• You read many papers or tutorials, understand topics deeply and have the creativity to translate them into RLVR problems.
• Proficiency in Python and systems programming; ideally PyTorch or JAX.
• Smart problem solvers who take ownership and drive solutions end-to-end.
• Passion for staying current with the rapidly evolving ML infrastructure landscape.
• Able to meet throughput expectations and respond quickly to feedback.
• Nice to have:
• Expert knowledge in an active DL/ML research area, with publications or public code to show for it.
• Research experience (PhD, MS) is a big plus.
• Deep understanding of transformer internals.
• Strong expertise in kernel development (CUDA, Triton, Pallas), optimizing non-trivial neural modules to specific hardware.
• Research projects, coursework, or personal work involving RL environments (any framework, any scale).
• Open-source contributions to ML infrastructure or RL tooling.
• Experience with any cloud platform (AWS, GCP, Azure) or infrastructure-as-code tools.

Benefits

• Competitive cash and equity compensation (>90th percentile)
• Ownership and autonomy in a fast-moving startup environment
• Opportunity to work with top machine learning engineers
• Health, vision, dental, benefits
• 401K match
• Lunch provided everyday onsite
• Weekly snack orders
• Visa sponsorship & relocation support available

Pay

$165K - $200K

Schedule

Flexible work schedule