Senior DL Algorithms Engineer - Inference Performance

Posted 2 Days Ago
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2 Locations
Remote
148K-288K
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The Senior DL Algorithms Engineer will optimize DL inference performance, analyze models, develop software tools, and collaborate with engineering teams.
Summary Generated by Built In

We are now looking for a Senior DL Algorithms Engineer! NVIDIA is seeking senior engineers who are mindful of performance analysis and optimization to help us squeeze every last clock cycle out of Deep Learning workloads. If you are unafraid to work across all layers of the hardware/software stack from GPU architecture to Deep Learning Framework to achieve peak performance, we want to hear from you! This role offers an opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution.

What you will be doing:

  • Deliver hyper-optimized recipes for DL inference as part of NVIDIA Inference Microservices (NIMs).

  • Analyze, validate and debug performance and accuracy characteristics of optimized models.

  • Benchmark state-of-the-art offerings in various DL models inference and perform competitive analysis for NVIDIA SW/HW stack.

  • Develop software, tooling and processes across multiple layers of the stack to streamline and scale the delivery of hundreds of optimized DL models.

  • Collaborate heavily with other SW/HW co-design teams to enable the creation of the next generation of AI-powered services.

What we want to see:

  • PhD in CS, EE or CSEE or equivalent experience.

  • 3+ years of experience.

  • Experience with delivering results under tight timelines and rapidly changing requirements.

  • Strong background in deep learning and neural networks, in particular inference.

  • Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture.

  • Programming skills in C++ and Python.

Ways to stand out from the crowd:

  • Strong fundamentals in algorithms.

  • Experience and good understanding of LLMs and/or VLMs, RAG, drug discovery models

  • Proven experience with processor and system-level performance modelling.

  • Experience with MLOps and DLOps, building CI/CD pipelines

  • GPU programming experience (CUDA or OpenCL) is a strong plus but not required.

As NVIDIA makes inroads into the Datacenter business, our team plays a central role in getting the most out of our exponentially growing datacenter deployments as well as establishing a data-driven approach to hardware design and system software development. We collaborate with a broad cross section of teams at NVIDIA ranging from DL research teams to CUDA Kernel and DL Framework development teams, to Silicon Architecture Teams. As our team grows, and as we seek to identify and take advantage of long term opportunities, our skillset needs are expanding as well. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!

The base salary range is 148,000 USD - 287,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse 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.

Top Skills

C++
Cuda
Opencl
Python
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The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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