GPU Engineer Team Leader

ACG_3671_JOB

Our client is a leading AI infrastructure software company, seeking an experienced professional to join their team.

Team Leadership & Delivery

• Lead, coach, and develop a team of 4–5 GPU/HPC engineers, promoting a culture of technical excellence, ownership, and continuous improvement.
• Plan and coordinate sprint activities, allocate workloads effectively, and ensure the timely delivery of high-quality GPU software components.
• Conduct regular one-on-one meetings, provide constructive feedback, and support the professional growth and career development of team members.
• Convert high-level technical objectives from senior engineers or engineering management into clear, executable tasks for the team.
• Monitor team progress, proactively identify and escalate blockers, and provide clear status updates to relevant stakeholders.

Hands-on Technical Contribution

• Develop production-grade GPU kernel code using CUDA, HIP, or OpenCL for AI training and inference workloads.
• Lead code review activities and uphold coding standards, GPU optimization practices, and software quality across the team.
• Perform performance profiling and optimization of GPU kernels, including memory hierarchy usage and execution efficiency.
• Contribute directly to technically complex features and resolve challenging issues that require deep expertise in GPU systems.

Requirements

Minimum Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or a related discipline.
• Strong proficiency in C++ and Python.
• Hands-on experience with CUDA, HIP, or OpenCL.
• Experience optimizing GPU memory hierarchies, including shared memory, registers, memory coalescing, and occupancy.
• Familiarity with deep learning frameworks such as PyTorch or TensorFlow, including their interaction with GPU computing environments.
• Proven experience leading or mentoring a small technical engineering team of at least two members.
• Strong analytical and problem-solving capabilities, with the ability to diagnose and resolve complex GPU software issues.
• Good written and verbal communication skills to support team coordination, documentation, and stakeholder communication.

Preferred Qualifications

• Master’s degree or Ph.D. in Computer Science, Computer Engineering, Artificial Intelligence, or a related field.
• At least two years of professional experience developing GPU system software.
• Experience with distributed GPU computing, multi-GPU coordination, or parallel runtime systems.
• Understanding of AI model architectures and their impact on GPU workload design, such as attention mechanisms and matrix operations.
• Demonstrated track record of owning end-to-end delivery for a team, module, or technical workstream.
• Experience using profiling tools such as Nsight Compute, Nsight Systems, or AMD ROCm Profiler.
• Contributions to open-source GPU/HPC projects or publications at relevant conferences such as PPoPP, HPDC, SC, MICRO, or similar venues.

Contact: Thao Phan and Thu Giang Van

Due to the immense number of applicants, only shortlisted candidates will be contacted