NVIDIA
Engineering Manager, AI Developer Technology
$224K–$356K
US, CA, Santa Clara +4 · Manager · Full-time · Posted Aug 5, 2026
- Location
- US, CA, Santa Clara
US, MA, Westford
US, TX, Austin
US, OR, Hillsboro
US, NC, Durham - Experience
- 8+ overall years of relevant experience, including 5+ years in a technical role and 3+ years in an engineering leadership role.
- Education
- MS or PhD in Computer Science, Computer Engineering, or a related computationally focused science or engineering degree (or equivalent experience).
About the job
Leads an AI Developer Technology team optimizing algorithms and real-world machine learning workloads for NVIDIA platforms, while driving technical initiatives and collaborating across teams and with customers.
What you'll do
- Lead development and optimization of machine learning and deep learning algorithms and workloads.
- Set and drive technical initiatives; collaborate with research, hardware, software teams, and customers on next-generation technology.
- Hire, coach, and grow the engineering team; communicate technical solutions and project plans.
What they ask for
- MS or PhD in Computer Science, Computer Engineering, or a related computationally focused science or engineering degree (or equivalent experience).
- 8+ years of relevant experience, including 5+ years in a technical role and 3+ years in engineering leadership.
- In-depth expertise in linear algebra and performance optimization of deep learning training and inference.
- Fluency in C/C++, background in parallel programming, and knowledge of CPU/GPU architecture and low-level performance optimization.
Nice to have
- PhD in a relevant field.
- Expertise in LLMs, multimodal model architecture, and performance optimization of relevant computational primitives; proven experience recruiting top talent.
Pay
224,000 USD - 356,500 USD base salary
Tools
CUDA, OpenMP, MPI, pthreads, C/C++
AI focus
Accelerates deep learning and machine learning training and inference, optimizes AI algorithms and workloads on NVIDIA hardware, and may work with LLMs, computer vision, speech, recommender systems, and multimodal architectures.
Model-written summary · the original posting is authoritative