Axiomaticai

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

Boston, Massachusetts, United States

Sponsorship not specifiedDetected 7 days ago
PythonNode.jsCloud PlatformsDockerKubernetesMachine LearningDeep LearningAccessibilityHardware DesignRF EngineeringResearchCommunication

About the role

  • We are looking for a scientific-computing engineer with deep experience in JAX, Julia, or other high-performance numerical-computing ecosystems.

Responsibilities

  • Build high-performance scientific-computing systems for simulation, inverse design, optimization, and uncertainty quantification in EDA-related workflows.
  • Develop and optimize JAX and/or Julia-based numerical pipelines, including differentiable solvers, adjoint methods, vectorized workloads, and GPU-accelerated computation.
  • Collaborate with scientists, engineers, and product teams to make advanced computational methods usable in real engineering workflows.
  • Cutting-Edge Tools: Access to state-of-the-art tools and collaborative opportunities with leading experts in artificial intelligence, physics, hardware and electronic design automation.
  • At Axiomatic_AI, you will be working on technology that drives innovation in AI for scientific and engineering applications in line with our 30 x 30 mission.

Requirements

  • Deep expertise in JAX or Julia.
  • Strong understanding of numerical methods, automatic differentiation, optimization, or scientific simulation workflows.
  • Experience profiling and optimizing numerical workloads on CPU and/or GPU.
  • Ability to reason about correctness, reproducibility, numerical stability, and performance trade-offs.
  • Clear communication skills and ability to work across software engineering, AI, mathematics, physics, and product teams.

Nice to have

  • Experience with distributed compute, job schedulers, multi-node workloads, Kubernetes, Docker, cloud infrastructure, or HPC systems.
  • Experience with lab automation, hardware-in-the-loop systems, PyVISA, SCPI, microcontrollers, FPGAs, or measurement equipment.
  • Competitive compensation
  • Professional Growth: Opportunities to attend industry conferences, present research findings, and engage with the global AI research community.
  • Impact-Driven Culture: Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware.
  • This is your opportunity to contribute to the development of new AI architectures that can reason coherently and produce interpretable and verifiable solutions.
  • We believe in pushing the boundaries of what is possible and continuously seek to redefine the intersection of AI, with focus on formal consistency.
  • If you're ready to take your expertise in artificial intelligence and physics to the next level, we want to hear from you!

Skills

  • differentiable simulation, optimization, uncertainty quantification, large-scale experiment execution, and reproducible numerical pipelines.

Compensation

  • Competitive compensation

Benefits

  • Stock Options Plan: Empowering you to share in our success and growth.
  • Work-Life Balance: Flexible work arrangements in one of our offices with potential options for remote work.

Company info

  • Axiomatic AI is building a new class of AI systems designed to reason with the rigor of the scientific method. By combining deep learning with formal logic and physics-based modeling, we create verifiable, interpretable AI systems that collaborate with and support human researchers in high-stakes scientific and engineering workflows.
  • Our mission, 30×30, is to deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030.
  • We aim to revolutionize hardware design and simulation in these industries and are building a team of highly motivated professionals to bring these innovations from research into commercial products.
  • Position overview:
  • Axiomatic AI is building a new class of AI systems designed to reason with the rigor of the scientific method.
  • By combining deep learning with formal logic and physics-based modeling, we create verifiable, interpretable AI systems that collaborate with and support human researchers in high-stakes scientific and engineering workflows.
  • We are building AI-assisted simulation and inverse-design tools for electronics, photonics, and semiconductor engineering.
  • You will build the computational backbone behind our EDA workflows: differentiable simulation, optimization, uncertainty quantification, large-scale experiment execution, and reproducible numerical pipelines.
  • You will work closely with AI engineers, software engineers, mathematicians, physicists, and domain experts to turn research-grade methods into robust production systems.
  • Open source is an important part of how we build.
  • We contribute upstream when it improves the tools our product depends on, but our primary mission is to deliver reliable, high-performance scientific software for real engineering users.
  • Your mission:
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This listing is sourced directly from Axiomaticai's careers page and normalized into a canonical job model.