Research Software Engineer — Differentiable Scientific Computing (JAX/Julia)

TL;DR

Research Software Engineer (Scientific Computing): Building AI-assisted simulation and inverse-design tools for electronics and semiconductor engineering with an accent on differentiable simulation and high-performance numerical pipelines. Focus on optimizing JAX/Julia workloads on GPU/CPU and translating research prototypes into production-grade services.

Location: Hybrid (Boston, US or Barcelona, Spain)

Company

hirify.global is building AI systems that combine deep learning with formal logic and physics-based modeling to revolutionize semiconductor and photonic hardware development.

What you will do

• Develop high-performance scientific-computing systems for simulation, inverse design, and optimization in EDA workflows.
• Optimize JAX and Julia numerical pipelines, including differentiable solvers and GPU-accelerated computation.
• Profile and improve performance across CPU/GPU backends, focusing on memory movement and distributed execution.
• Build verification infrastructure, including numerical regression tests and benchmark suites.
• Transform research prototypes into stable APIs and production-grade services.
• Collaborate with scientists, physicists, and product teams to integrate computational methods into engineering workflows.

Requirements

• 3+ years of experience building scientific, numerical, ML infrastructure, or HPC software.
• Deep expertise in JAX or Julia.
• Strong Python and/or Julia engineering skills, including package design, CI, and testing.
• Solid understanding of numerical methods, automatic differentiation, and optimization.
• Proven experience profiling and optimizing numerical workloads on CPU and/or GPU.
• Strong communication skills for cross-functional collaboration.

Nice to have

• Experience in EDA, photonics, semiconductor design, or multiphysics simulation.
• Knowledge of distributed compute, Kubernetes, Docker, or HPC systems.
• Experience building QA frameworks for scientific or ML systems.
• Familiarity with lab automation, FPGAs, or measurement equipment.

Culture & Benefits

• Competitive compensation and Stock Options Plan.
• Access to state-of-the-art AI and physics tools.
• Flexible work arrangements with a hybrid office model.
• Professional growth opportunities including industry conferences and research presentations.
• Impact-driven culture focused on solving complex hardware-AI intersection problems.