Research Scientist

Connect with me and feel free to apply if you’re a Researcher or Machine Learning Engineer and aren’t sure you’re the perfect fit.

I’m currently working with two elite, well-funded teams in the Bay Area (SF \& Palo Alto) that are taking Reinforcement Learning in polar opposite, but equally ambitious, directions:

1\. The Foundational Research Lab (San Francisco)

Founded by "old-school" RL PhDs, this lab believes the field is scaling prematurely while ignoring core issues like data inefficiency and long action horizons. Backed by

Vercel and South Park Commons

, they are building a research-driven environment to scale RL-LLM hybrids by orders of magnitude.

• The Mission:

Moving past DPO/RLHF to create agents that genuinely generalize.

• The Team:

Talent from

DeepMind, Meta, and NVIDIA

.

2\. The "Ground Truth" Reasoning Startup (Palo Alto)

A

Stanford spinout

solving for long-horizon reasoning by moving RL into a space where physics and logic provide a non-negotiable ground truth:

Chip Design.

They are building a "Cursor for Verilog" where agents must plan, critique, and verify their own code against real execution feedback.

• The Mission:

Collapsing the 3-year hardware design cycle through automated reasoning.

• The Team:

Led by the former

Head of AI (Trust \& Safety) at Anthropic

, with peers from

xAI and OpenAI

.

• The Backing:

Top-tier VCs with support from figures like Jeff Dean.

Both teams are looking for "founding-level" engineers who can ship production-grade systems, not just run experiments.

If either of these philosophies:

foundational scaling

or

physical verification

align with where you want to take your next career move, feel free to apply.