Physics Simulation Engineer

Job Summary:

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.

Location: Greater Boston-Providence, RI Preferred

We are seeking a candidate preferably based in the greater Boston area willing to commute periodically to Providence, the location of our core operations, other developers and facilities. However, exceptional candidates located elsewhere will also be considered.

Responsibilities:

• 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.

Qualifications:

Essential

• MS or PhD in physical sciences, engineering, or computer science, with a focus in Scientific Machine Learning
• Strong expertise and intuition for modeling physical systems and using numerical solvers (e.g. Finite Element Methods)
• Minimum of 4 years of industry experience in physics-based simulation and analysis
• Education in and/or experience applying Machine Learning algorithms
• Experience in agile software development on a team (i.e. not just individual research development)
• Strong analytical and problem-solving skills, with the ability to translate complex physical phenomena into computational models.
• Excellent communication skills to effectively convey technical concepts to diverse stakeholders.
• Proficiency in Python, along with JAX, PyTorch, and/or TensorFlow

Preferred

• Strong preference for published papers on the application of SciML
• Experience in working with customers on building algorithms, codes, and/or tools for solving real-world problems
• Experience in code development in a production environment.
• Experience with release trains at a certain cadence, delivering on time and with high quality.
• Familiarity with high-performance computing (HPC) environments and parallel computing techniques.

Job Type: Full-time

Pay: $125,000.00 - $145,000.00 per year

Benefits:

• Dental insurance
• Health insurance

Application Question(s):

• Do you have a published paper on the application of Scientific ML?
• Have you worked on numerical solvers before (e.g. Finite Element or Finite Differences)?
• What commercial simulation solver software have you used? Please list all.

Experience:

• JAX, PyTorch, and/or Tensorflow: 4 years (Preferred)

Work Location: Remote