HPC Nonlinear Solid Mechanics Software Engineer

Getvinci; Palo Alto (CA); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Equity participation

Flexible work environment

Job summary

Vinci4d is recruiting a software engineer at the intersection of computational solid mechanics, numerical methods, and HPC. You will design, implement, and tune solvers for nonlinearities in solid mechanics that run at scale on modern hardware.

This role emphasizes building new capabilities, not maintaining old stacks, and requires collaboration with physicists, engineers, and software developers to deliver robust, high-performance tooling.

Qualifications

• Hands-on experience developing solvers for geometric and material nonlinearity in solid mechanics.
• Strong FEM foundation for solid and structural mechanics.
• Experience with Krylov methods and preconditioning for large sparse systems.
• Proven GPU programming experience (CUDA/HIP/SYCL) with real performance gains.
• Proficiency in C++ and/or Python in performance-critical codebases.

Responsibilities

• Develop and tune nonlinear solvers for solid mechanics with large deformation and history-dependent constitutive models.
• Build and optimize underlying linear algebra: iterative solvers and preconditioners for large sparse systems.
• Port and optimize solvers for GPU execution with memory bandwidth and scalability focus.
• Implement FEM discretizations for structural and thermomechanical solves with robustness under ill-conditioned conditions.
• Contribute to software engineering foundations: version control, automated testing, CI/CD, code reviews.

Skills

Nonlinear solvers

Finite element method

GPU programming

C++/Python

Iterative solvers

CI/CD practices

Performance optimization

Job description

Vinci4d is recruiting a software engineer at the intersection of computational solid mechanics, numerical methods, and HPC. You will design, implement, and tune solvers for nonlinearities in solid mechanics that run at scale on modern hardware.

This role emphasizes building new capabilities, not maintaining old stacks, and requires collaboration with physicists, engineers, and software developers to deliver robust, high-performance tooling.