Manager, GPU Accelerated Data Analytics

at Nvidia

USD 224,000-431,200 per year

SENIOR

✅ Hybrid

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Algorithms @ 7 CUDA @ 4 Communication @ 6 GPU @ 4 Hiring @ 4 Leadership @ 7 Networking @ 6 Parallel Programming @ 4 Performance Optimization @ 4 SQL @ 7 Software Development @ 7 Vector Databases @ 7

Details

NVIDIA's Developer Technology Engineering team is a global network of experts advancing accelerated computing. The team develops solutions that help developers leverage NVIDIA's CPUs, GPUs, and software platforms across cloud and on-premise environments.

This role leads a team of performance engineers working with the developer community to optimize complex workloads, including databases, data preprocessing, compression, video transcoding, and web servers. The position focuses on modernizing data centers through performance-focused software and algorithm development for NVIDIA platforms.

Responsibilities

Research, analyze, and develop innovative techniques to optimize complex workloads across cloud and on-premise environments.
Develop new algorithms and work with hardware architects to improve performance for workloads that are difficult to parallelize.
Lead software design decisions and influence architecture roadmaps.
Prioritize and lead initiatives that advance the performance and adoption of NVIDIA hardware and software platforms.
Build and mentor a distributed team of performance engineers.
Grow domain, hardware, and software expertise within the team.
Collaborate with company leadership, research teams, and cross-functional partners on strategic decision-making, program management, and initiative execution.
Advocate for next-generation hardware and software products that address developer needs.

Requirements

MS or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree, or equivalent experience.
7+ years of relevant experience, including 4+ years in a technical role and 3+ years in an engineering leadership role.
Outstanding leadership, cross-functional collaboration, and project execution skills.
Hands-on experience with low-level performance optimization, including GPU parallel programming such as CUDA.
Fluency in C/C++ and deep understanding of algorithms and software development.
In-depth knowledge of CPU and GPU architecture fundamentals.
Strong algorithmic skills and experience implementing low-level optimizations for enterprise applications.
Experience building high-performing teams by attracting and hiring engineering talent.
Excellent communication and presentation skills.
Ability to plan, lead, and execute high-impact initiatives.

Preferred Qualifications

PhD in a relevant field.
Experience leading engineering teams in designing performance-first prototypes.
Strong background in distributed, high-performance data analytics, including SQL or vector databases.
Expertise in modern data center networking and storage technologies.

Benefits

Equity and employee benefits are available.
NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.

Applications for this job will be accepted at least until March 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.