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ML Engineer, Foundation Models

1 hour, 3 minutes ago
United States
Full-time
Senior
Machine Learning Engineer
Software Development
Machine Learning PyTorch Reinforcement Learning
Apply Now
Lever

Lever

Lever is a leading Talent Acquisition Suite that provides modern hiring and talent management solutions. Their applicant tracking system (ATS) with candidate relationship management capabilities empowers hiring teams to streamline recruiting efforts an...

Professional Services
251-1K
Founded 2012
$123M raised
View All Jobs 5

Description

  • Design and iterate on the vision-language-action model architecture, including the VLM backbone, action decoder, and multimodal fusion pipeline.
  • Build and optimize large-scale training infrastructure, including distributed training, data pipelines, mixed-precision, and efficient fine-tuning.
  • Develop simulation-based evaluation and closed-loop training workflows using photorealistic neural rendering.
  • Curate and manage multimodal training datasets spanning real-world driving and synthetic scenarios.
  • Translate research in diffusion, flow matching, reasoning-augmented VLAs, and world models into production-grade systems.
  • Collaborate with vehicle systems and controls engineers to integrate model outputs into a real-time autonomous driving stack.
  • Support architecture decisions, large-scale training, simulation evaluation, and deployment on trucks across the full model development lifecycle.

Requirements

  • MS or PhD in Computer Science, Machine Learning, Robotics, or a related field, or equivalent industry experience.
  • Strong proficiency in PyTorch, distributed training, and GPU-accelerated workflows.
  • Solid foundation in transformer architectures, attention mechanisms, and modern generative modeling, including diffusion and flow matching.
  • Eligible to work in the United States.
  • Experience building or contributing to end-to-end autonomous driving systems (preferred).
  • Track record of publications at top ML/robotics venues such as NeurIPS, ICLR, ICRA, or CoRL, or significant open-source contributions (preferred).
  • Familiarity with sim-to-real transfer, photorealistic simulation, or neural rendering for driving scenes (preferred).
  • Experience with reinforcement learning, imitation learning, or learning from demonstration in embodied settings (preferred).
  • Comfort operating as an early team member with high ownership, low ego, and fast iteration (preferred).

Benefits

  • Base salary plus benefits and equity compensation.
  • Salary determined by role, level, location, qualifications, skills, and experience.
  • Opportunity to join a small, fast-moving team building an autonomous freight system from the ground up.
  • AI-assisted interview process with human review of all AI output.
  • Equal opportunity employer consideration for qualified applicants.
  • Consideration of qualified applicants with arrest and conviction records consistent with local ordinances.

Interested in this position?

Apply directly on the company website

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