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"Lead Research Software Engineer, Portable AI Performance Engineering"

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Lead Research Software Engineer, Portable AI Performance Engineering

Staff

May 17, 2026

Location

Massachusetts

MA Green High Performance Computing Center

Type

Full-time, 2-year term (remote/hybrid)

Required Qualifications

Bachelor’s + 5 years experience
Python & C++ proficiency
PyTorch/TensorFlow/JAX
GPU programming (CUDA/HIP)
Performance profiling on Linux HPC
Excellent communication

Research Areas

AI Performance Engineering
GPU Optimization (AMD MI355X)
ROCm/HIP Porting
High-Performance Computing
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Lead Research Software Engineer, Portable AI Performance Engineering

Posting Description

LEAD RESEARCH SOFTWARE ENGINEER, PORTABLE AI PERFORMANCE ENGINEERING, MA Green High Performance Computing Center, to be a hands-on research software engineering professional and serve as lead for applied performance engineering for AI workloads. Will work closely with research groups and leading computer industry collaborators to evaluate, adapt, and enhance the portable performance of complex AI research workloads on state-of-the-art hardware. The role will have heavy focus on optimizing existing NVIDIA GPU-based workloads for top-tier AMD GPUs, such as MI355X and beyond and will analyze and profile existing research AI workloads to identify performance bottlenecks and portability challenges; and port and optimize complex AI models and scientific code to run efficiently on AMD MI355X GPUs using ROCm, HIP, and related translation tools.

Job Requirements

REQUIRED: Bachelor’s degree or equivalent with a minimum of five years of work experience in either deeply technical fields and/or computational research experience; strong proficiency in Python and C++, with deep familiarity with AI/ML frameworks (PyTorch, TensorFlow, JAX); hands-on experience with GPU programming models (e.g., CUDA, HIP, or OpenCL); experience with performance profiling and benchmarking tools on Linux-based High-Performance Computing systems; excellent communication skills; ability to collaborate effectively with academic researchers and industry partners; and self-motivated with the ability to work independently in a remote or hybrid environment. PREFERRED: Direct experience with the AMD ROCm software stack and translating CUDA code to HIP; familiarity with AI agentic tools and Large Language Models (LLMs) used for code generation and refactoring; background in supporting large-scale, domain-specific scientific research (e.g., physics, biology, climate science) on institutional clusters; direct experience with one or more open-source schedulers and provisioners; experience with Linux container technologies such as LXC, apptainer and systemd-nspawn; or advanced degree in a relevant technical field.

The Lead Software Engineer must comply with all relevant MGHPCC security policies.

This is a two-year term position.

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Frequently Asked Questions

🎓What are the required qualifications for this Lead Research Software Engineer role?

Candidates need a Bachelor’s degree or equivalent with at least five years in technical or computational research fields. Key skills include strong Python and C++ proficiency, deep knowledge of AI/ML frameworks like PyTorch, TensorFlow, and JAX, hands-on GPU programming (e.g., CUDA, HIP), and experience with performance profiling on Linux HPC systems. Excellent communication and collaboration skills are essential. Check research jobs for similar roles.

🔧What preferred experience is valued for AI performance engineering?

Preferred: Direct experience with AMD ROCm stack and CUDA to HIP translation, familiarity with AI agentic tools and LLMs for code generation, background in domain-specific science (physics, biology, climate), open-source schedulers, Linux containers (LXC, Apptainer), or an advanced degree. Explore postdoc research tips to build these skills.

🏠Is this position remote or hybrid, and what's the employment term?

This is a two-year term position with flexibility for remote or hybrid work. Self-motivation is key for independent operation. Comply with MGHPCC security policies. View remote higher ed jobs for more options.

What are the main responsibilities in portable AI performance engineering?

Lead applied performance engineering for AI workloads: Profile and optimize NVIDIA GPU code for AMD MI355X GPUs using ROCm, HIP, and tools. Collaborate with researchers and industry on portability challenges. Ideal for administration jobs in HPC.

🤝How does this role support collaboration and industry partners?

Work closely with academic researchers and industry collaborators (e.g., leading computer firms) to enhance AI research workloads on state-of-the-art hardware. Strong communication is required. Learn more via employer branding advice for partnering in higher ed.

📅When is the application deadline for this MGHPCC software engineer job?

Applications are open until May 17, 2026. Prepare your resume highlighting GPU optimization and HPC experience. Use our free resume template for academic jobs.
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