Member of Technical Staff - Staff Engineer, Multimodal Pre-Training

Walden Robotics

$318K — $425K *
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of hands-on experience with large models like LLM, VLM, or multimodal systems at scale.
  • Proven ability to train models on multiple objectives or modalities, integrating language and vision-language.
  • Practical experience in generative modeling techniques for images and videos, as well as world-modeling for physical dynamics.
  • Strong understanding of scaling laws, distributed training, and troubleshooting large model failures.
  • Ability to set technical direction and prioritize effectively under uncertainty.

Responsibilities

  • Drive the pre-training agenda for omni-models across diverse objectives.
  • Train a single model balancing various losses at a massive scale.
  • Lead efforts in architecture design, tokenization, and scaling-law analysis.
  • Prepare large-scale datasets for training with data and infrastructure teams.
  • Enhance training reliability, mentor team members, and integrate cutting-edge ideas quickly.

Benefits

  • Competitive total compensation including cash bonuses and equity.
  • Company-subsidized insurance programs for employees.
  • 401(k) plan with company match to support retirement savings.
  • Flexible PTO policy to promote work-life balance.
  • Daily lunch provided for employees.
Full Job Description
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 is for salary only.

The pay range for this role is:

318,750 - 425,000 USD per year (BOS)

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