Senior Research Engineer, CFD Algorithm Development

About the Role

SandboxAQ is seeking a hands-on computational scientist or engineer to lead the CFD Algorithm Development Project. This role involves developing and deploying a differentiable Computational Fluid Dynamics (CFD) framework on multi-GPU and multi-node systems to optimize chemical reactor designs.

The ideal candidate will combine strong technical depth in CFD, GPU programming, and differentiable simulation with practical experience in model validation and high-performance computing (HPC). You will be responsible for delivering several critical milestones that advance our mission of building AI-driven, physics-based optimization tools for next-generation catalytic reactors.

• Lead development of differentiable CFD solvers for non-isothermal and reactive flow simulations on mulit-node multi-GPU hardware using JAX
• Design, implement, and containerize code to ensure reproducibility, scalability, and ease of deployment across HPC GPU environments.
• Develop optimized parallel linear solvers using FFT or other matrix decompositions
• Extend existing implementation of immersed boundary method to complex geometries and non-periodic boundary conditions
• Extend and validate CFD capabilities from single-node to multi-node GPU systems for both non-reactive and reactive flow regimes.
• Integrate transport equations for up to 50 chemical species using linear numerical methods.
• Validate simulation accuracy against benchmark results and fixed-bed reactor configurations.
• Develop gradient-based optimization scripts to iteratively modify reactor designs based on objective functions defined by catalyst activity and selectivity.
• Collaborate closely with AI model developers to link catalyst property predictions with reactor-scale flow optimization.
• Generate comprehensive technical reports summarizing algorithms, scalability, differentiability, and validation results for milestone reviews.

• PhD or MS in Computation Physics, Mechanical or Chemical Engineering,  Computer Science or equivalent discipline.
• 3+ years (including PhD) of hands-on experience in CFD code development, preferably on GPUs
• Proven expertise building scalable scientific software on multi-GPU systems using JAX, PyTorch, CUDA, MPI frameworks or similar.
• Full fluency across all of:  numerical linear algebra, numerical methods for solving PDEs, sparse and dense linear solvers, immersed boundary methods
• Excellent Python programming skills, with experience in JAX a prerequisite
• Ability to work independently, manage multiple deliverables, and produce clear technical documentation.

• PhD + 3 years industry experience in Computational Physics, Mechanical/Chemical Engineering, Computer Science or related field
• Proven expertise in CFD code development for non-isothermal flow, transport equations, and reactive flow modeling.
• Proven expertise with differentiable computational fluid dynamics, and/or gradient-based optimization of complex CFD objectives (i.e. adjoint optimization, auto-diff a.s.o)
• Proven experience across the full stack of scientific software development including PR submission, code review, unit-testing, integration testing, containerization with Docker and enroot,, and deployment on GPU-HPC systems using k8s, Google Cloud Batch, slurm or similar.
• Proven expertise in chemical reactor and multi-physics modeling (e.g., reactive flow, energy and mass transport in fixed-bed or catalytic systems).
• Demonstrated track record of delivering project milestones and publishing high-quality technical results.