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Nvidia Data Scientist Jobs in Raleigh, NC (NOW HIRING)

Senior HPC and LSF Operations Engineer

Durham, NC · Hybrid

$101K - $138K/yr

Analyze scheduler and infrastructure performance data to identify systemic bottlenecks and drive ... Bachelor's degree in Computer Science or related field, or equivalent experience * Minimum 5+ years ...

Senior Software Engineer, Agentic AI

Durham, NC · On-site

$118K - $156K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Work closely with teams building high-performance data pipelines, RAG systems, vector databases ...

Senior Site Reliability Engineer - HPC

Durham, NC · On-site

$55 - $73.25/hr

NVIDIA has been transforming computer graphics and accelerated computing for over 25 years. They ... S. degree in Computer Science or related technical field (or equivalent experience) with 5+ years ...

Senior Software Engineer - HPC

Durham, NC · Hybrid

$118K - $156K/yr

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Improve uptime and Quality of Service (QoS) through data-driven operations, strong SLOs, and robust ...

Senior AI Performance Architect

Raleigh, NC · On-site

$162K/yr

At the same time, data centers are expanding AI capability through widespread deployment of ML ... In-depth knowledge of nVidia/AMD GPU capabilities and architectures * Knowledge of LLM ...

... Functions, API Gateway, Data Science, Autonomous Database, and Oracle Integration Cloud ... Experience with LangChain, LangGraph, NVIDIA NIM, or Hugging Face * Experience leading AI or ERP ...

Showing results 41-51

Nvidia Data Scientist information

See Raleigh, NC salary details

$44.7K

$160.4K

$236.7K

How much do nvidia data scientist jobs pay per year?

As of Aug 10, 2026, the average yearly pay for nvidia data scientist in Raleigh, NC is $160,402.00, according to ZipRecruiter salary data. Most workers in this role earn between $129,800.00 and $165,200.00 per year, depending on experience, location, and employer.

Is a Nvidia Data Scientist job still in demand?

Nvidia Data Scientist roles remain in high demand due to the company's focus on AI, machine learning, and deep learning technologies. These positions often require expertise in programming, data analysis, and familiarity with Nvidia's tools like CUDA and GPU computing, making them valuable in industries such as technology, automotive, and healthcare.

What is a Nvidia data scientist?

A Nvidia Data Scientist leverages AI, machine learning, and deep learning to develop models and algorithms that optimize GPU-accelerated computing solutions. They work with large datasets, conduct research, and build scalable data-driven solutions for industries like gaming, autonomous vehicles, and healthcare. Their role involves collaborating with engineers and researchers to improve AI frameworks and performance on Nvidia hardware. Proficiency in Python, deep learning frameworks (TensorFlow, PyTorch), and data analytics is essential.

What are the key skills and qualifications needed to thrive as a Nvidia data scientist, and why are they important?

To thrive as an Nvidia Data Scientist, you need a solid background in statistics, machine learning, computer science, and typically a graduate degree in a related field. Proficiency with Python, deep learning frameworks (such as TensorFlow or PyTorch), GPU computing, and experience with large-scale data systems are highly valued, along with relevant certifications. Analytical thinking, strong problem-solving abilities, and clear communication are soft skills that set candidates apart in this collaborative, fast-evolving field. These capabilities are essential for driving innovation, building robust AI solutions, and contributing effectively to cross-functional teams at Nvidia.

What types of projects does a Nvidia data scientist typically work on, and how do they contribute to the company's core technologies?

Nvidia Data Scientists are often involved in pioneering projects related to AI model development, computer vision, natural language processing, and deep learning applications optimized for GPU hardware. They collaborate closely with research engineers, software developers, and product teams to create scalable AI solutions that enhance Nvidia’s products, ranging from gaming to autonomous systems. A typical week might involve experimenting with new algorithms, analyzing large datasets, optimizing code for GPU acceleration, and translating research breakthroughs into practical applications. This role offers continuous learning opportunities and plays a direct part in shaping industry-leading technologies.

What are the most commonly searched types of Nvidia Data Scientist jobs in Raleigh, NC? The most popular types of Nvidia Data Scientist jobs in Raleigh, NC are:
What are popular job titles related to Nvidia Data Scientist jobs in Raleigh, NC? For Nvidia Data Scientist jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Nvidia Data Scientist jobs in Raleigh, NC look for? The top searched job categories for Nvidia Data Scientist jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Nvidia Data Scientist jobs? Cities near Raleigh, NC with the most Nvidia Data Scientist job openings:
Infographic showing various Nvidia Data Scientist job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, and 6% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $160,402 per year, or $77.1 per hour.

Senior HPC and LSF Operations Engineer

Nvidia

Durham, NC • Hybrid

$101K - $138K/yr

Full-time

Re-posted 23 hours ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies


Job description

As a member of the Hardware Infrastructure EDA Compute team, you will optimize, scale, and support workload scheduling systems that directly impact design velocity and infrastructure efficiency. Success in this role requires both operational precision along with developing and supporting forward-looking resource management solutions that address evolving compute demands. Beyond day-to-day operations, the role drives improvements in observability, service reliability, and automation, ensuring the EDA compute environment remains resilient, measurable, and aligned with long-term engineering demands.


What you'll be doing:

  • Manage, scale, and optimize job scheduling systems (LSF, Slurm, etc.) in a large-scale, multi-site environment supporting EDA and other compute-intensive workloads

  • Analyze scheduler and infrastructure performance data to identify systemic bottlenecks and drive measurable improvements in utilization, throughput, and turnaround time

  • Lead problem solving across scheduler, OS, and workload layers, ensuring timely resolution of service-impacting issues

  • Identify recurring operational challenges and implement targeted automation or process improvements to reduce manual effort and prevent repeat incidents

  • Help define and track reliable metrics and SLOs for service performance and reliability, partnering with customers to ensure expectations are realistic and measurable

  • Contribute to operational standards, documentation, and best practices to improve consistency across sites

  • Partner directly with customer teams to clarify requirements, translate technical tradeoffs, and drive issues to closure


What we need to see:

  • Bachelor's degree in Computer Science or related field, or equivalent experience

  • Minimum 5+ years of experience operating and supporting large-scale Linux-based compute infrastructure

  • Strong hands-on experience supporting and tuning job scheduling systems (LSF, Slurm, etc.) in HPC or silicon design environments

  • Proficiency in Linux systems administration (CentOS/RHEL)

  • Strong problem solving skills and the ability to independently analyze complex system behavior under load

  • Clear and effective communication skills, including the ability to articulate technical tradeoffs and reliability metrics to engineering stakeholders


Ways to stand out from the crowd:

  • Experience implementing reliability engineering practices within HPC scheduling environments

  • Deep knowledge of job scheduling systems (LSF, Slurm, etc.) configuration tuning, scheduler internals, and advanced troubleshooting techniques

  • Experience building or enhancing observability systems, including metrics collection, monitoring pipelines, alerting strategies, and performance dashboards

  • Background with container technologies such as Docker, Singularity, or Podman in HPC environments

  • Experience influencing adoption of new infrastructure standards across multiple teams or sites


NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most forward-thinking and hardworking people in the world on our team and our collaborative talent continues to drive NVIDIA's growth. We are seeking creative and independent engineers with real passion for technology!
#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 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 July 24, 2026.

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.

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Pay

Benefits

Hours and flexibility

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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