Senior Developer Technology Engineer - Windows LLM & GenAI Open-Source Ecosystem at NVIDIA

Würselen, North-Rhine-Westphalia, Germany

Apply Now

Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, TechnologyIndustries

Requirements

5+ years of professional experience in local GPU deployment, profiling and optimization
BS or MS degree in Computer Science, Engineering, or related degree
Strong proficiency in C/C++, Python, software design, programming techniques
Familiarity with and development experience on the Windows operating system
Proven theoretical understanding of Transformer architectures - specifically LLMs and Generative AI - and convolutional neural networks
Experience working with open-source LLM and GenAI software
Experience with CUDA and NVIDIA's Nsight GPU profiling and debugging suite
Strong verbal and written communication skills in English and organization skills, with a logical approach to problem solving, time management, and task prioritization skills
Excellent interpersonal skills
Some travel is required for conferences and for on-site visits with external partners

Responsibilities

Improve Windows LLM & GenAI user experience on NVIDIA RTX by working on feature and performance enhancements of OSS software, including but not limited to projects like GGML, Llama.cpp, Ollama, ONNX Runtime
Engage with internal product teams and external OSS maintainers to align on and prioritize OSS enhancements
Work closely with internal engineering teams and external app developers on solving local end-to-end LLM & Generative AI GPU deployment challenges, using techniques like quantization or distillation
Apply powerful profiling and debugging tools for analyzing most demanding GPU-accelerated end-to-end AI applications to detect insufficient GPU utilization resulting in suboptimal runtime performance
Conduct hands-on trainings, develop sample code and host presentations to give good guidance on efficient end-to-end AI deployment targeting optimal runtime performance
Guide developers of AI applications applying methodologies for efficient adoption of DL frameworks targeting maximal utilization of GPU Tensor Cores for the best possible inference performance
Collaborate with GPU driver and architecture teams as well as NVIDIA research to influence next generation GPU features by providing real-world workflows and giving feedback on partner and customer needs
Contribute to the LLM & GenAI open-source ecosystem to enable Windows AI enthusiasts and developers with innovative models and functionality as well as speed-of-light performance on RTX
Engage with strategic partners and internal teams to overcome the challenges arising when deploying modern LLM & GenAI architectures on local workstations

Skills

Key technologies and capabilities for this role

WindowsLLMGenAIRTXGGMLLlama.cppOllamaONNX RuntimequantizationdistillationGPU accelerationprofilingdebugging

Questions & Answers

Common questions about this position

What is the salary for this Senior Developer Technology Engineer position?

This information is not specified in the job description.

Is this role remote or does it require working from a specific location?

The role is based with the team in Wuerselen.

What skills and experience are required for this position?

Candidates need 5+ years of professional experience in local GPU deployment, profiling and optimization, a BS or MS in Computer Science or related field, strong proficiency in C/C++, Python, and software design, familiarity with Windows OS development, proven understanding of Transformer architectures like LLMs and GenAI, and experience with open-source LLM and GenAI software.

What kind of team will I be working with at NVIDIA?

You'll work closely with internal product teams, engineering teams, GPU driver and architecture teams, NVIDIA research, external OSS maintainers, strategic partners, and app developers.

What makes a strong candidate for this Developer Technology Engineer role?

A strong candidate has 5+ years in GPU deployment, profiling, and optimization, expertise in C/C++ and Python, Windows development experience, deep knowledge of LLMs and GenAI architectures, and hands-on work with open-source projects like GGML or Llama.cpp.

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

Land your dream remote job 3x faster with AI

Try Jobo Free