Senior Research Engineer (Hardware Accelerators)

Code Metal is redefining code translation for mission-critical industries, helping defense partners move more quickly and reliably from algorithm to silicon. They are seeking a Research Engineer specializing in programming of hardware accelerators to design and develop code transpilation and optimization pipelines for various hardware accelerators such as GPUs and FPGAs.

Responsibilities:

• Work closely with the research and engineering team to build code transpilation and optimization pipelines for various hardware accelerators. At least one of the source and target languages would be accelerator-specific (such as CUDA, HIP, SYCL). The source language could also be a generic language such as Python or C/C++
• Understand the architecture of the target hardware and propose optimization strategies that would accelerate given input code
• Analyze performance of the input as well as the transpiled code to determine optimization strategies
• Integrate hardware specific tools (compilers, profilers, libraries, etc.) in the transpilation and optimization pipelines
• Conduct experiments to evaluate performance of code transpilation and optimization pipelines. Analyze experimental results to improve pipelines further
• Collaborate across multidisciplinary teams, contributing to both research initiatives and production-grade solutions
• Present research findings in a broader audience group

Requirements:

• 5+ years of industry experience and an advanced degree (Master's or Ph.D.) in Computer Science, Mathematics, or a related field, with a focus on software engineering, high-performance computing, and parallel programming languages
• Strong programming skills in Python and C/C++
• Good understanding of parallel programming languages: CUDA/OpenCL/OpenMP/SYCL
• Good understanding of popular hardware devices such as CPUs and GPUs
• Understanding of AI-specific hardware accelerators such as NPUs is a plus
• Good understanding of common performance analysis practices
• Demonstrated proficiency in core software development practices, including: version control, code review, testing, continuous integration, build systems, and release pipelines
• Combination of strong software engineering skills with a solid background in high-performance computing to build robust and maintainable systems
• Ability to translate technical research into practical engineering solutions
• Excellent communication skills and a collaborative mindset
• Understanding of the latest AI-specific hardware accelerators such as NPUs, Google TPUs
• Familiarity with deep learning frameworks such as PyTorch and TensorFlow
• Experience integrating parallel programming tools into CI/CD pipelines or software development workflows
• Contributions to related open-source projects
• Experience working in high-assurance industries (e.g., aerospace, medical devices, automotive)