Key Facts

Remote From:

Canada, California (USA), United States

Full time

English

Hard Skills

AI/ML Inference PyTorch (Machine Learning Library) C++ (Programming Language) GPU Optimization Deep Learning Computer Architecture Debugging Software Quality Management Language Model GPU Optimization Performance Systems Analysis OpenCL Nvidia CUDA Cross-Functional Collaboration Software Development

Other Skills

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Communication
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Teamwork
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Problem Solving

Roles & Responsibilities

PhD in CS, EE or CSEE or equivalent experience
3+ years of professional experience in deep learning and neural networks, particularly inference
Experience with performance profiling, analysis and optimization for GPU-based applications
Proficiency in C++, PyTorch or equivalent frameworks

Requirements:

Implement language and multimodal model inference as part of NVIDIA Inference Microservices (NIMs)
Contribute new features, fix bugs and deliver production code to TRT-LLM, NVIDIA's open-source inference serving library
Profile and analyze bottlenecks across the full inference stack to push the boundaries of inference performance
Benchmark state-of-the-art DL model inference and perform competitive analysis for NVIDIA SW/HW stack

Job description

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:

Implement language and multimodal model inference as part of NVIDIA Inference Microservices (NIMs).
Contribute new features, fix bugs and deliver production code to TRT-LLM, NVIDIA’s open-source inference serving library.
Profile and analyze bottlenecks across the full inference stack to push the boundaries of inference performance.
Benchmark state-of-the-art offerings in various DL models inference and perform competitive analysis for NVIDIA SW/HW stack.
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.
Strong background in deep learning and neural networks, in particular inference.
Experience with performance profiling, analysis and optimization, especially for GPU-based applications.
Proficient in C++, PyTorch or equivalent frameworks.
Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture.

Ways to stand out from the crowd:

Proven experience with processor and system-level performance optimization.
Deep understanding of modern LLM architectures.
Strong fundamentals in algorithms.
GPU programming experience (CUDA or OpenCL) is a strong plus

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 148,000 USD - 235,750 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 10, 2026.

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.

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