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 @ 6 CUDA @ 4 Deep Learning GPU @ 4 Leadership @ 6 Mentoring Parallel Programming @ 4 Performance Optimization @ 4 SQL @ 7 Software Development @ 7 Technical Leadership @ 6 Vector Databases @ 7

Details

NVIDIA's Developer Technology Engineering team is a global network of world-class experts pushing the boundaries of accelerated computing. The team empowers developers with groundbreaking solutions while driving innovation that fuels NVIDIA's leadership in this transformative field. NVIDIA's accelerated computing platform is revolutionizing industries.

This role offers a unique opportunity to lead a team of skilled performance engineers collaborating directly with the developer community to unlock the full potential of NVIDIA's groundbreaking CPUs and GPUs. NVIDIA's accelerated computing platform is known for its AI dominance in deep learning training and inference. Nonetheless, modern data centers have hundreds of millions of CPUs that are used today to run mission critical workloads such as database, data preprocessing, compression, video transcoding, web servers, and many others. Help modernize today’s data centers by researching and developing implementations to help save cost and power using the advanced NVIDIA platform.

What you’ll be doing

Responsibilities

Driving Innovation: Research, analyze, and develop innovative techniques to optimize performance of complex workloads across cloud and on-premise environments. These workloads are difficult to parallelize and major performance speed-ups require inventing new algorithms and working side-by-side with architects to influence hardware.
Technical Leadership: Drive technical excellence by leading software design decisions, influencing architecture roadmap, and effectively communicating technical solutions to multi-functional teams. Prioritize and lead key initiatives that advance the performance and adoption of NVIDIA’s hardware and software platforms.
Growing and Mentoring Your Team: Build a distributed world-class team of performance engineers. Grow domain, hardware and software expertise within your team to strengthen external developer engagements. Foster a collaborative and innovative culture that encourages idea sharing, empowers team members, and provides opportunities for professional growth.
Collaboration and Communication: Collaborate closely with company leadership, research teams, and cross-functional partners to drive strategic decision-making, program management, and successful initiative implementation. Advocate for next-generation hardware and software products that address the evolving needs of the developer community.

What we need to see

An MS or PhD in Computer Science, Computer Engineering, or in a related computationally focused science degree (or equivalent experience).
7+ overall years of relevant experience with 4+ years in a technical role and 3+ years of experience in an engineering leadership role.
Outstanding leadership, strong cross-functional collaboration, and impactful project execution.
Hands-on experience in low-level performance optimization, including GPU parallel programming (e.g., CUDA).
Programming fluency in C/C++ with a deep understanding of algorithms and software development.
In-depth expertise with CPU and GPU architecture fundamentals.
Strong algorithmic skills and proven experience implementing low-level optimizations for enterprise applications.
A track record of building high-performing teams by attracting and hiring top engineering talent.
Excellent communication and presentation skills.
Demonstrated ability to successfully plan, lead, and execute high-impact initiatives.

Ways to stand out from the crowd

A PhD in a relevant field is highly valued.
Experience leading engineering teams to design performance-first prototypes.
Strong background in distributed high-performance data analytics including SQL or vector databases.
Expertise in modern data center network and storage technologies.

Base salary and eligibility

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD for Level 3 and 272,000 USD - 431,250 USD for Level 4.

You will also be eligible for equity and benefits.