Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Algorithms @ 4
Performance Optimization @ 4
Microservices @ 4
LLM @ 4
PyTorch @ 6
CUDA @ 1
GPU @ 4
Deep Learning @ 4
AI @ 4
Profiling @ 4
OpenCL @ 1
Performance Analysis @ 4
- 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.
Details
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.
Responsibilities
- 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.
Requirements
- PhD in CS, EE or CSEE or equivalent experience.
- 5+ 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 plus.
Compensation & Benefits
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 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits (see NVIDIA benefits page).
Additional information
Applications for this job will be accepted at least until February 22, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer.