AI DevTech Engineering Manager — ML/DL Performance Lead

NVIDIA AI; Durham (NC); On-site; USD 224,000 - 356,500; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking an AI Developer Technology Engineering Manager in the US to lead a team accelerating DL/ML workloads on NVIDIA platforms. You will define technical initiatives, collaborate with research and hardware teams, and hire and grow a high-performing group focused on optimized algorithms for real-world AI tasks.

You will guide development, communicate design decisions, and promote engineering excellence while driving impact across product and research ecosystems.

Qualifications

• An MS or PhD in Computer Science, Computer Engineering, or related field (or equivalent).
• 8+ years total experience with 5+ years technical and 3+ years in leadership.
• Strong expertise in linear algebra and DL/ML performance optimization.
• Background in parallel programming (CUDA, OpenMP, MPI, pthreads, etc.).
• Fluent C/C++ and knowledge of CPU/GPU architecture fundamentals.

Responsibilities

• Lead your team to optimize and develop ML/DL algorithms.
• Define and drive technical initiatives advancing accelerated DL/ML.
• Collaborate with research, hardware, and software teams on future designs.
• Develop and communicate technical solutions, plans, and decisions.
• Hire and grow a diverse, high-performing team.
• Coach and promote engineering excellence and idea proliferation.

Skills

MS/PhD in CS/CE

8+ years experience

5+ years in technical role

3+ years engineering leadership

Deep DL performance optimization

Parallel programming (CUDA, OpenMP,MPI

C/C++ programming

Excellent written/presentation skills

Proven track record of initiative

Education

MS/PhD in CS or Engineering

Tools

CUDA

OpenMP

MPI

pthreads

Job description

NVIDIA is seeking an AI Developer Technology Engineering Manager in the US to lead a team accelerating DL/ML workloads on NVIDIA platforms. You will define technical initiatives, collaborate with research and hardware teams, and hire and grow a high-performing group focused on optimized algorithms for real-world AI tasks.

You will guide development, communicate design decisions, and promote engineering excellence while driving impact across product and research ecosystems.