Foundation Models

Genesis Therapeutics
London, United Kingdom
Hybrid

Who this role is best for

Aimed at senior machine learning researchers and engineers who build end-to-end models for robotics control and curate large-scale datasets.

Best fit for

  • Senior ML researchers with a track record of full-stack foundation model work and independent problem-solving
    — “Exceptional ownership and initiative—finding and solving problems independently”
  • Candidates with 5+ years of impactful research and a focus on data and code quality
    — “A relentless commitment to data and code quality, rigorous evaluation, and meticulous attention to detail”
  • Individuals experienced in generative simulation techniques and embodied perception
    — “Design new generative simulation techniques to expand simulation data scale and diversity”

Things to consider

  • Candidates must have 5+ years of experience in pioneering or refining ML methods
    — “Extensive experience pioneering new machine learning ideas or refining existing methods”

How to stand out

  • Highlight experience with full-stack foundation model development and deployment in your resume and interviews
    — “Passion for your craft and demonstrated excellence in full-stack foundation model research and engineering”
  • Emphasize your ability to curate and manage large-scale, high-quality datasets
    — “Collaborate with simulation and real-world robotics teams to curate high-quality, diverse, and large-scale datasets”
  • Showcase your expertise in generative models for 3D environments and task generation
    — “Training and evaluating generative models of 3D objects and environments”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • build machine learning models for robotics control
  • curate high-quality datasets
  • design new generative simulation techniques
Typical background
machine learningroboticsdata curation

Skills & requirements

Required

Robotics ControlData CurationModel ArchitectureTraining/inference StacksRigorous Experiments

Preferred

Vision-language-action ModelsEmbodied PerceptionVideo Generation

About the role

Original posting from Genesis Therapeutics via Ashby

What You'll Do

  • Build machine learning models for robotics control end-to-end: data curation, careful evaluation, model architecture, training/inference stacks, rigorous experiments
  • Collaborate with simulation and real-world robotics teams to curate high-quality, diverse, and large-scale datasets
  • Curate the world’s best Internet-scale datasets for embodied perception and first-person robot video generation
  • Design new generative simulation techniques to expand simulation data scale and diversity, training and evaluating generative models of 3D objects and environments, and language/code models to generate tasks and reward functions
  • Collaborate with a team of driven individuals committed to building general-purpose Physical AI

What You'll Bring

  • Passion for your craft and demonstrated excellence in full-stack foundation model research and engineering
  • Exceptional ownership and initiative—finding and solving problems independently
  • Extensive experience pioneering new machine learning ideas or refining existing methods, supported by first-author publications or impactful projects (5+ years)
  • A relentless commitment to data and code quality, rigorous evaluation, and meticulous attention to detail
  • Production-level expertise in modern Python
  • Bonus: Experience with Vision-Language-Action models for robotics or web agents, embodied perception, or video generation

Source: Genesis Therapeutics careers (Ashby)

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