We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the ...
We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the ...
Senior AI Systems Engineer
Raleigh, NC · On-site +1
$92K - $126K/yr
Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar. * Experience with simulations for scientific or engineering projects ...
Senior AI Systems Engineer
Raleigh, NC · On-site +1
$92K - $126K/yr
Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar. * Experience with simulations for scientific or engineering projects ...
Senior AI Systems Engineer
Raleigh, NC · On-site +1
$92K - $126K/yr
Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar. * Experience with simulations for scientific or engineering projects ...
Senior AI Systems Engineer
Raleigh, NC · On-site +1
$92K - $126K/yr
Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar. * Experience with simulations for scientific or engineering projects ...
Senior Software Engineer, CUTLASS Performance
$118K - $156K/yr
Hands-on experience with performance benchmarking of DL frameworks like PyTorch, JAX, SGLang, vLLM, TRT-LLM, or others. * Experience in developing performance models and performance regression ...
Senior Software Engineer, CUTLASS Performance
$118K - $156K/yr
Hands-on experience with performance benchmarking of DL frameworks like PyTorch, JAX, SGLang, vLLM, TRT-LLM, or others. * Experience in developing performance models and performance regression ...
Senior AI Systems Engineer
Raleigh, NC · On-site
$92K - $126K/yr
Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar. * Experience with simulations for scientific or engineering projects ...
Senior AI Systems Engineer
Raleigh, NC · On-site
$92K - $126K/yr
Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar. * Experience with simulations for scientific or engineering projects ...
Optimize inference performance - latency, throughput, quantization, and deployment efficiency - for production, including frameworks such as vLLM, TensorRT-LLM, or TGI. Small language models & open ...
Optimize inference performance - latency, throughput, quantization, and deployment efficiency - for production, including frameworks such as vLLM, TensorRT-LLM, or TGI. Small language models & open ...
Vllm information
How does a VLLM (Very Large Language Model) Engineer typically collaborate with data scientists and product teams during model deployment?
VLLM Engineers work closely with data scientists to understand the specific requirements and fine-tuning needs of large-scale language models. They are often responsible for integrating these models into production systems, ensuring scalability and efficiency. Collaboration with product teams is crucial to align model capabilities with user needs and to troubleshoot real-world application challenges. Frequent communication and agile workflows are common, as updates or optimizations may be needed rapidly based on feedback from both teams.
What is a VLLM and what do they do?
VLLM stands for 'Virtual Large Language Model.' In the context of AI development, VLLM professionals work with optimized inference engines for large language models, enabling faster and more efficient deployment of AI models in production environments. Their responsibilities often include integrating LLMs into applications, optimizing model performance, and ensuring scalability for real-time use cases. They may also collaborate with data scientists and engineers to manage resources and streamline AI workflows.
What is the difference between Vllm vs Data Analyst?
| Aspect | Vllm | Data Analyst |
|---|---|---|
| Required Credentials | Typically requires knowledge of machine learning, AI, and programming languages like Python or R | Requires skills in statistics, Excel, SQL, and data visualization tools |
| Work Environment | Often in tech companies, research labs, or AI-focused teams | Commonly in business, finance, healthcare, and marketing sectors |
| Industry Usage | Emerging role in AI and machine learning projects | Established role in data-driven decision making |
| Common Search/Comparison | Vllm vs Data Analyst |
The main difference between Vllm and Data Analyst lies in their focus and skill set. Vllm professionals specialize in AI and machine learning models, often working in tech environments, while Data Analysts focus on interpreting data to inform business decisions. Both roles require analytical skills, but Vllm roles demand programming and AI expertise, whereas Data Analysts emphasize statistical analysis and data visualization.
What are the key skills and qualifications needed to thrive as a Machine Learning Engineer working with vLLM, and why are they important?
To thrive as a Machine Learning Engineer specializing in vLLM (a high-throughput LLM inference library), you need a strong understanding of machine learning principles, deep learning frameworks, and experience with Python programming. Familiarity with tools like PyTorch, CUDA, distributed computing, and cloud platforms, as well as relevant certifications in ML or data engineering, is highly valuable. Strong problem-solving, collaboration, and communication skills are essential for optimizing model performance and integrating with cross-functional teams. These capabilities ensure effective deployment and scaling of large language models, driving innovation and efficiency in AI applications.
What are popular job titles related to Vllm jobs in Raleigh, NC? For Vllm jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Vllm jobs in Raleigh, NC look for? The top searched job categories for Vllm jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Vllm jobs? Cities near Raleigh, NC with the most Vllm job openings:
Job description
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.
We are looking for a motivated Deep Learning engineer to bring advanced communication technologies into AI stacks, including PyTorch, TRT-LLM, vLLM, SGLang, JAX, etc. You will be working with the team that created communication libraries like NCCL, NVSHMEM & technology like GPUDirect -- for scaling Deep Learning and HPC applications. Your customers will have diverse multi-GPU demands, ranging from training on scales up to 100K GPUs to inference down at microsecond latency. Communication performance between the GPUs has a direct impact on AI applications. Your work in AI toolkits will make all of those easier for the community. This is an outstanding opportunity for someone with an AI background to advance the state of the art in this space. Are you ready to contribute to the development of innovative technologies and help realize NVIDIA's vision?
What you will be doing:
Integrate new communication libraries features in AI frameworks: from PoC to performance analysis to production
Perform deep analysis of AI workloads and frameworks to identify multi-GPU communication requirements and opportunities. Collaborate hands-on with teams working on the latest AI models.
Improve AI compilers to hide communications or perform automatic fusion.
Conduct in-depth AI workload performance characterization on multi-GPU clusters.
Design fault-tolerant and elastic solutions for large-scale or dynamic AI workloads.
Author custom communication or fused compute-communication kernels to showcase ultimate performance on NV platforms.
Influence the roadmap of communication libraries - NCCL & NVSHMEM.
Collaborate with a very dynamic team across multiple time zones.
What we need to see:
B.S, M.S. or PHD in Computer Science, or related field (or equivalent experience) with 5+ software engineering and HPC/AI experience
Development or integration experience with Deep Learning Frameworks such PyTorch, JAX, and Inference Engines such as TRT-LLM, vLLM, SGLang
Rapid prototyping and development with Python, C++, CUDA or related DSLs (Triton, cuTe)
Solid grasp of AI models, parallelisms, and/or compiler technologies (e.g. torch.compile)
Experience conducting performance benchmarking on AI clusters. Familiarity with at least one performance profiler toolchain (PyTorch profiler, NVIDIA Nsight Systems)
Understanding of HPC/AI communication concepts (1-sided v 2-sided communication, elasticity, resiliency, topology discovery, etc)
Adaptability and passion to learn new areas and tools
Flexibility to work and communicate effectively across different teams and timezones
Ways to stand out from the crowd:
Experience with parallel programming on at least one communication runtime (NCCL, NVSHMEM, MPI). Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)
Expertise in one or more of these areas: Training, Distributed inference, MoE, Reinforcement Learning, kernel authoring (on CUDA, Triton, cuTe, etc). Experience with programming for compute & communication overlap in distributed runtimes
Experience with AI compiler pattern matching and lowering. Solid understanding of memory hierarchy, consistency model, and tensor layout
You will also be eligible for equity and benefits.
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.
About Nvidia
Sourced by ZipRecruiter
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.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Santa Clara, CA, US
Year founded
1993