Position Summary:You'll be a senior technical leader for how our foundation models become capable, aligned robot policies. Working alongside our AI leadership and world-class team, you'll drive key work across SFT, preference optimization (RLHF/DPO-style), distillation, and RL-with success measured by policies that act more reliably on real robots in the real world.
Core Responsibilities:- Post-Training Strategy: Help shape the post-training recipe-SFT, preference tuning (RLHF/DPO-style), distillation, and RL-and own key stages of how each turns a strong base model into a deployable policy.
- Reasoning, Tool Use & Multimodality: Push grounded reasoning, tool use, and multimodal understanding for models that must act in the world, not only answer.
- Behavior & Alignment: Align model behavior with product and safety requirements across diverse tasks and embodiments.
- Evaluation Methodology: Strengthen the eval and experimentation methodology that separates real gains from noise-spanning offline metrics and on-robot performance.
- Technical Leadership: Set the technical bar for post-training, mentor the team, and partner with data teams on what data most improves behavior.
Required Qualifications:- Post-Training Depth: Deep hands-on experience post-training large multimodal models-SFT, RLHF/DPO-style preference methods, distillation-with results you have shipped or published.
- Reinforcement Learning: Strong command of RL for large models (reward modeling, policy optimization) and its practical failure modes.
- Frontier-Scale Models: Experience working with multimodal LLMs or VLA models at frontier scale.
- Program Ownership: A record of owning end-to-end model-improvement programs and setting technical direction others follow.
- Measurement & Grounding: Excellent judgment about what to measure, and the instinct to debug across the stack.
Preferred Qualifications:- Experience with embodied AI, robotics, or vision-language-action models (or strong desire to move from LLMs into the physical world).
- Familiarity with evaluating open-ended, real-world task performance.
- Contributions to influential models, papers, or open-source post-training stacks.
Walden Robotics offers a competitive total compensation program, including salary, annual cash bonus, company equity, company-subsidized insurance programs, 401(k) with company match, flexible PTO, daily lunch, and other benefits. The pay ranges noted on our posts are for salary only.
The pay range for this role is:
318,750 - 425,000 USD per year (BOS)
318,750 - 425,000 USD per year (SF)
