Easy Apply
Be an Early Applicant
Machina Labs is introducing unseen flexibility and agility to the centuries-old manufacturing industry.
The Role
Seeking a Research Engineer with a PhD or equivalent experience to develop physics simulation algorithms and collaborate on AI-driven manufacturing solutions.
Summary Generated by Built In
Company
Machina Labs is a smart manufacturing company backed by leading investors in AI and Deep Tech (Innovation Endeavors, Nvidia NVentures, Lockheed Martin Ventures), founded in 2019 and based in Los Angeles, CA. We are building the factory of the future with modular manufacturing solutions that allow customers to rapidly produce and iterate on their designs using our robotic sheet metal forming platform. Our first-of-its-kind software and robotics solution brings new levels of innovation to industries such as aerospace, automotive, and space exploration.
About the Role
We are seeking a Research Engineer with strong expertise in computational science, computer graphics, and robotics to help shape the next generation of AI-driven manufacturing systems. This position combines fundamental research with applied engineering, offering the opportunity to design novel physics-based solvers, explore differentiable and real-time simulation techniques, and contribute to cutting-edge developments in robotics and embodied AI. You will collaborate with a team of researchers and engineers to translate innovative computational ideas into scalable frameworks that enhance both scientific understanding and real-world manufacturing capabilities.
What You'll Do:
- Formulate and implement novel physics simulation algorithms tailored to robotic sheet metal forming, grounded in first-principles modeling.
- Develop and analyze advanced numerical methods for PDEs, contact modeling, deformation, and multi-physics coupling.
- Build high-performance simulation software leveraging GPU acceleration (CUDA, Warp, Taichi, or similar).
- Collaborate with ML, robotics, and manufacturing engineers to ensure physical fidelity and integration with control and learning systems.
- Explore novel approaches, such as differentiable simulation, reduced-order modeling, and multi-scale methods, for enabling real-time decision-making.
- Contribute to high-quality, modular codebases that support reproducible research and production deployment.
- Disseminate results through publications in leading venues, bridging fundamental research and high-impact industrial applications.
What We're Looking For:
- PhD (or Master's with equivalent research experience) in Computer Science, Computational Mechanics, Applied Mathematics, or a related field.
- Strong research background in scientific computing, computer graphics, and robotic simulations.
- Demonstrated experience developing high-performance simulation frameworks.
- Proficiency in C++ and Python, with expertise in parallel computing and GPU acceleration.
- Knowledge of finite element methods, material point methods, or other physics-based solvers.
- Proven publication record in top venues such as SIGGRAPH, SIGGRAPH Asia, Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering, ICRA, IROS, RSS, CoRL, or related conferences and journals.
- Ability to work at the intersection of fundamental research and real-world system development.
Bonus:
- Experience applying physics-based simulations in robotics, control, or manufacturing settings.
- Familiarity with NVIDIA Omniverse, Warp, or Taichi.
- Track record of advancing state-of-the-art algorithms from research prototypes to impactful engineering solutions.
Why This Role Matters
This is a key research-focused role where you’ll define and build the core simulation technologies enabling intelligent manufacturing systems of the future.
Your contributions will push the boundaries of computational physics for robotics, directly influencing how machines learn, plan, and act in complex real-world environments. The technology developed here has the potential to transform smart manufacturing and accelerate progress toward embodied AI, where robots possess a deeper physical understanding of the world.
Machina Labs is an Affirmative Action and Equal Employment Opportunity employer and considers all applicants for employment without regard to race, color, religion, sex, gender identity, gender expression, sexual orientation, national origin, age, disability, or status as a protected veteran in accordance with state and federal law.
We endeavor to make the job application process accessible to any and all users. If you have a disability that impacts your ability to complete the job application process and would like to request assistance or a reasonable accommodation, please contact us at (888)444-9777. This contact information is for accommodation requests only, not to inquire about the status of applications.
Top Skills
C++
Cuda
Python
Taichi
Warp
What the Team is Saying
Jessica
Office Manager
Mark
Process Development Manager
Edward
CEO
Joakim
Machine Learning Engineer
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
This unlocks rapid iteration improving design lifecycle and enabling a higher rate of innovation. Machina Labs’ manufacturing platform combines the latest advances in robotics and AI so great ideas can quickly and affordably turn to reality.
Why Work With Us
Machina Labs unlocks manufacturing with AI & Robotics. Machina's Robotic Craftsman is introducing unseen flexibility and agility to the centuries-old manufacturing industry, enabling rapid iteration and innovation to design, engineering, and production. Machina helps leading companies quickly and affordably turn great ideas into reality.
Gallery
Machina Labs, Inc Offices
OnSite Workspace
Most employees work in-person at our beautiful office in Chatsworth, CA. Some employees engage in a combination of remote and on-site work.
Typical time on-site:
None
Los Angeles, CA
