Research Scientist V

Crystal Equation Corporation; California (MO); Hybrid; USD 109,000 - 116,000; Full time

Benefits offered by this job

Paid time off

Medical insurance

Dental insurance

Vision insurance

Life insurance

401K

Parental leave

And more

Job summary

Crystal Equation Corporation seeks a Research Scientist V to advance physics-based rewards for post-training generative video models using reinforcement learning. You will own the reward signal, drive performance across three workstreams, and extend capabilities to human-object and human-scene interaction with 3D mesh representations.

The role requires expertise in rigid-body simulation, 3D pose representations, and Python/PyTorch optimization, with a PhD/MS in a relevant field or equivalent

Qualifications

• MS/PhD in robotics, graphics, mechanical engineering or CS, or equivalent industry experience

Responsibilities

• Owns a physics-based motion reward used to post-train generative video models via reinforcement learning.
• Three workstreams: improving the reward signal terms; making the reward cheap enough to run inside the loop at scale; extending it from single-body plausibility to human-object and human-scene interaction using 3D mesh representations.

Skills

Rigid-body simulation

3D pose & motion

Python/PyTorch

Reward design/post-training

Numerical methods

Education

MS/PhD in robotics/graphics/mechanical engineering or CS

Tools

MuJoCo

Isaac

Bullet

SMPL-family

Job description

Research Scientist V Remote

Responsibilities

Owns a physics-based motion reward used to post-train generative video models via reinforcement learning. Three workstreams: improving the dynamic and contact terms of the reward signal; making the reward cheap enough to run inside the loop at scale rather than as an offline filter; and extending it from single-body plausibility to human-object and human-scene interaction using 3D mesh representations.

Required Skills

• Rigid-body/contact simulation (MuJoCo, Isaac, Bullet or equivalent)
• 3D human pose and motion representations (SMPL-family)
• Python/PyTorch with profiling and optimization of compute-heavy pipelines
• Reward design and post-training of large generative models
• Numerical methods and solver stability

Required Qualifications

MS/PhD in robotics, graphics, mechanical engineering or CS, or equivalent industry experience

Preferred Qualifications

• Publications in physics-grounded generative modeling or differentiable simulation
• Generative video/diffusion experience
• Scaling simulation workloads
• Validating simulated physical quantities against human-judged ground truth

Pay

Pay range is $79 - $84 per hour with full benefits available.

Benefits

• paid time off
• medical/dental/vision/life insurance
• 401K
• parental leave
• and more

Our compensation reflects the cost of labor across several US geographic markets. Pay is based on several factors including market location and may vary depending on job-related knowledge, skills, and experience.

THE PROMISES WE MAKE

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