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Simulation Engineer

2 months, 2 weeks ago
United States
Full-time
Mid Level
Research Scientist
Artificial Intelligence and Machine Learning
Machine Learning Python
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 4

Description

  • Build and maintain Python pipelines and tooling for closed-loop testing and synthetic data generation.
  • Integrate neural rendering techniques into the sensor simulation stack, including Gaussian splatting, NeRFs, and world models.
  • Expand and maintain the scenario library and benchmark suite used to evaluate perception, planning, and control.
  • Develop synthetic data generation workflows, including scenario and agent behavior generation, to support model training.
  • Work with ML and autonomy engineers to measure and reduce sim-to-real gaps.
  • Help ensure simulation reflects real-world behavior and supports model validation.
  • Contribute to the design of systems and tools in a small, early-stage team.
  • Influence both what the team builds and how it builds it.

Requirements

  • BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field, or equivalent industry experience.
  • Strong proficiency in Python, the primary language of the simulation stack.
  • Experience working with simulation systems, ideally in robotics, autonomous vehicles, or other high-fidelity domains.
  • Eligible to work in the United States.
  • Experience with neural rendering or generative simulation, such as Gaussian splatting, NeRFs, world models, or diffusion-based methods (preferred).
  • Depth in one or more simulation areas such as closed-loop testing, scenario design, log replay, or sensor simulation (preferred).
  • Experience building benchmarks or evaluation frameworks used across a team (preferred).
  • Experience developing synthetic data pipelines that improved downstream model performance (preferred).
  • Familiarity with real-time robotic systems and their simulation fidelity constraints (preferred).
  • Comfort working on a small team with high ownership and fast iteration cycles (preferred).

Benefits

  • Base salary plus benefits plus equity compensation.
  • Salary range determined by role, level, and location.
  • Individual pay considers qualifications, skills, experience, and location.
  • Equal opportunity employer with inclusive hiring practices.

Interested in this position?

Apply directly on the company website

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