Research Scientist, AI & Systems Co-Design (PhD)

What you'll do

• Co-design and optimize parallelism, algorithms, deployment techniques, and ML kernels for AI training and serving.
• Benchmark and model AI workloads to guide future hardware, models, runtimes, and software-stack design.
• Lead cross-functional technical initiatives from prototyping through productionization.

What they ask for

• PhD in Computer Science, Electrical Engineering, Applied Mathematics, or a related technical field (completed or near completion).
• Bachelor’s degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience; degree must be completed before joining.
• Research experience in one or more listed areas, including computer architecture, ML systems and kernels, ML compilers, or model-system co-design.
• Hands-on AI hardware architecture or on-device mapping algorithm development, plus system-level AI workload analysis, profiling, and benchmarking experience.

Nice to have

• Experience with Python and at least one major AI framework; familiarity with CUDA, HIP, Triton, or hardware description languages.
• Experience or knowledge of distributed ML, large-scale model training/inference, GenAI or recommendation models, and AI agents.

Pay

$122,000/year to $181,000/year (base salary)

Tools

Python, CUDA, HIP, Triton, HDL, Transformers, LLMs, Diffusion models

AI focus

AI systems research and co-design, including model optimization, ML kernels, distributed training and inference, model serving, hardware efficiency, and performance analysis for generative AI and recommendation workloads.