Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. We are Seeking a Software Engineering Manager for our applied research team within NVIDIA’s Networking Systems & Software Architecture group. This role will be based in Santa Clara, CA. This team is solving some of AI’s hardest infrastructure problems. The team builds systems-level software that moves data between GPUs, nodes, and storage at the speed modern AI demands—spanning low-level transport optimization, hardware-software co-design, and communication frameworks that plug directly into production AI stacks. The team's charter expands into emerging domains including quantum computing interconnects. This Engineering Manager role leads a team responsible for that work—owning execution, and setting technical direction. It calls for someone technically strong enough to drive architecture and focused on creating an extraordinary engineering organization! What you will be doing: • Lead and develop a team of systems and networking engineers building distributed AI communication systems—libraries, frameworks, and system integrations. • Build the technical roadmap in partnership with principal engineers and architects, balancing near-term delivery with long-term research bets. • Create a culture of technical excellence and open collaboration. Handling project planning, resource allocation, and delivery timelines across concurrent workstreams. What we need to see: • 8+ overall years of software engineering experience with advanced knowledge in systems software, networking, or distributed systems. This experience allows credible participation in architecture reviews and making informed trade-off decisions. • 3+ years of direct people management experience. • BS, MS, PhD or equivalent experience in Computer Science, Computer Engineering, or a related field. • Ability to scope a problem, set a plan, and deliver results in a fast-paced R&D environment. • Strong communication skills—comfortable speaking publicly, writing technical documents, and giving candid feedback. • Good understanding of computer architecture, memory hierarchies, DMA engines, and networking. • Proficiency in programming languages such as C, C++, Rust and Python. • Understanding of ML systems concepts—transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns. Ways to stand out from the crowd: • Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements. • Familiarity with hardware and software ecosystems. • Experience with agile methodologies adapted for engineering teams dedicated to research. This role is born out of the unprecedented growth in this segment of the industry, our engineering teams are experience rapid demand increases. If you're a creative and autonomous engineer with a real passion for technology, we want to speak with you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 2, and 224,000 USD - 356,500 USD for Level 3. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until July 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

Must-haves

Lead and develop a team of systems and networking engineers building distributed AI communication systems—libraries, frameworks, and system integrations.
Build the technical roadmap in partnership with principal engineers and architects, balancing near-term delivery with long-term research bets.
Create a culture of technical excellence and open collaboration. Handling project planning, resource allocation, and delivery timelines across concurrent workstreams.
3+ years of direct people management experience.
BS, MS, PhD or equivalent experience in Computer Science, Computer Engineering, or a related field.
Ability to scope a problem, set a plan, and deliver results in a fast-paced R&D environment.
Strong communication skills—comfortable speaking publicly, writing technical documents, and giving candid feedback.
Good understanding of computer architecture, memory hierarchies, DMA engines, and networking.
Proficiency in programming languages such as C, C++, Rust and Python.
Understanding of ML systems concepts—transformer architectures, KV cache mechanics, model parallelism, or distributed training and inference patterns.
Knowledge of ML inference frameworks (vLLM, SGLang, TensorRT-LLM) and their communication requirements.
Familiarity with hardware and software ecosystems.
Experience with agile methodologies adapted for engineering teams dedicated to research.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until July 25, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

airustpythonmlllmagile

Platform: eightfold
Effort: medium

Benefits

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