JOIN OUR TEAM

Phinyx AI was born in George Karniadakis’s lab at Brown University, the birthplace of Scientific Machine Learning and a hub for groundbreaking advancements in Scientific Computing. Endorsed by Subra Suresh, former MIT Dean of Engineering and Director of NSF, we are a team of world-class computer scientists and physicists on a mission to redefine the landscape of engineering simulations.

By fusing generative AI with powerful scientific computing techniques, we’ve developed a cutting-edge engine capable of solving complex, multi-physics, and multi-dimensional engineering problems. Our mission is to make the most advanced engineering and simulation tools accessible to all design and engineering teams.

The future of engineering is digital and software-driven, and at Phinyx, we believe that a team of computational PhDs should be empowered to innovate. Join us to help shape this future and make cutting-edge simulation tools available to all.

WHAT WE OFFER

Competitive Compensation

We offer a competitive compensation package designed to attract and retain the best minds in the industry.

Medical Insurance

Comprehensive health coverage, including medical, dental, and vision, ensures you and your family are well-protected.

Paid Time Off

Enjoy generous paid time off to recharge and maintain a healthy work-life balance.

Remote Friendly

We offer remote, in-office, and hybrid options, giving you the freedom to work in the way that best suits your life.

Make Your Mark

The chance to make a significant impact and actively shape the direction of an early-stage company.

401K

We offer a 401k retirement plan to help you build long-term financial security.

PHINYX AI OPENINGS

PHYSICS SIMULATION ENGINEER

Greater Boston-Providence, RI Preferred | FULL-TIME

We are seeking an experienced Physics Simulation Engineer to help deliver cutting edge Scientific Machine Learning Methods with out Generative AI technology. The ideal candidate will be able to leverage commercial simulation tools in addition to developing custom solvers and scientific computing methods. Application domains will span fluid dynamics, thermals, structural mechanics, and more.

Translate real-world engineering problems into computational approaches across the scientific machine learning domain, classical scientific computing, optimization, and many more.
Support and advance the development of scientific components for simulation and machine learning capabilities across the Phinyx platform (numerical solvers, surrogate models, optimization algorithms, and other ML models)
Utilize commercial simulation software (e.g., Ansys, COMSOL) as needed to solve problems. Experience using software/scripting interfaces preferred.
Develop and demonstrate the methodology for making the aforementioned computational capabilities accessible through advanced AI-driven program synthesis. Leverage deep technical understanding of the methods to envision and define proper abstractions.

APPLY