Senior Member of Technical Staff: Multimodal Pre-Training in Cambridge

Position Summary

You'll be a senior technical leader for the pre-training of the omni-models at the core of our stack—single models trained across a wide range of objectives and modalities (LLM, VLM, video, and action) at massive scale.

Working alongside our AI leadership and world-class team, you'll help set the research agenda, own high-impact architecture, objective, and data-mixture bets, and help push how far these base models scale.

Core Responsibilities

• Pre-Training Roadmap: Help drive the pre-training agenda for omni-models spanning language, vision-language, video, and action, in close partnership with the AI team.
• Omni-Model Objectives: Train a single model across a wide range of losses (LLM, VLM, video and image generation) at massive scale, and decide how to weight and balance them.
• Core Modeling: Lead modeling work across architecture, tokenization, and the scaling-law analysis behind compute allocation.
• Data & Infrastructure: Turn petabyte-scale text, image, and video data into training-ready mixtures with the data and infra teams.
• Technical Leadership: Help raise the bar on training reliability and evaluation, support and mentor teammates, and bring frontier ideas into our stack quickly.

Required Qualifications

• Large-Scale Pre-Training: Deep, hands-on experience pre-training large models—LLM, VLM, multimodal, or VLA—at significant scale, with concrete results.
• Multi-Objective

Training: Experience training across multiple objectives or modalities—e. g. combining language, vision-language, and generative video/image losses—and balancing them in one model.

• Generative & World

Models: Hands-on experience with generative modeling of images and/or video (diffusion, autoregressive, or masked objectives) and/or world-model approaches to physical dynamics.

• Scaling & Systems: Fluency with scaling laws, distributed training, and the practical failure modes of massive runs, and the ability to design around them.
• Technical Direction & Judgment: A track record of setting direction others build on, moving fluidly between research and production-grade code, and prioritizing ruthlessly under uncertainty.

Preferred Qualifications

• Experience pre-training LLMs or VLMs at scale.
• Experience training video-generation, image-generation, or world-model systems at scale.
• Experience with action/robotics modalities or VLA models for embodied agents.
• Contributions to widely used models, influential papers, or open-source 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.

Walden Robotics is an equal opportunity employer.

All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations, and ordinances.

If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to hello@waldenrobotics. com

Walden Robotics participates in E-Verify.

If you receive an offer of employment from Walden, you will need to go through the E-Verify process of digital verification of your employment authorization documents as provided on the Form I-9.

Participation in E-Verify does not limit your right to work and verification will only be completed after you become