Machine Learning Compiler

Qualcomm•Raleigh, NC

46d

About The Position

Lead a team of engineers focused on advancing machine learning compiler technologies for cutting-edge AI accelerators for the Cloud and Datacenter market. This role combines deep technical expertise with strategic leadership to deliver high-performance compiler solutions that enable next-generation AI workloads.

Requirements

Bachelor's degree in Computer Science, Electrical Engineering, or related field and 10+ years of relevant experience; OR
Master's degree and 8+ years of experience; OR
Ph.D. and 6+ years of experience in compiler development, ML systems, or related areas.
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
Master's degree in Computer Science, Engineering, Information Systems, or related field and 5+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field and 4+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Nice To Haves

Strong background in compiler design (LLVM, optimization passes, IR transformations).
Expertise in ML frameworks (PyTorch, ONNX) and graph-level optimizations.
Familiarity with ML hardware accelerators, memory hierarchies, and performance modeling.
Solid C++ programming skills
Proven ability to lead teams and deliver complex software projects in fast-paced environments

Responsibilities

Drive innovation in ML compiler optimization algorithms, leveraging advanced mathematics, programming language theory, and modern compiler techniques.
Oversee feature design, code reviews, and integration of compiler components into the AI software stack.
Ensure robust testing, profiling, and performance tuning across diverse ML models and hardware targets.
Manage and mentor a team of engineers, fostering technical growth and collaboration.
Plan and execute projects to meet release deliverables, balancing tactical improvements with strategic roadmap goals.
Coordinate cross-functional efforts with hardware, architecture, and AI framework teams.
Shape the evolution of ML compiler technology within the organization, aligning with industry trends and internal product strategies.

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