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How much do ai phd computer science jobs pay per year?

As of Sep 10, 2026, the average yearly pay for ai phd computer science in the United States is $126,612.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,000.00 and $153,000.00 per year, depending on experience, location, and employer.

What is an AI PhD in computer science?

An AI PhD in Computer Science is a doctoral program focused on advanced research in artificial intelligence within the broader field of computer science. Students in this program work on developing new algorithms, models, and theories to advance the understanding and application of AI. The program typically involves coursework, original research, and the completion of a dissertation. Graduates often pursue careers in academia, research labs, or industry, contributing to innovations in machine learning, robotics, natural language processing, and more.

What are the key skills and qualifications needed to thrive as an AI PhD in computer science?

To thrive as an AI PhD in Computer Science, you need deep expertise in machine learning, mathematics, algorithm design, and a doctoral degree in computer science or a closely related field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong analytical thinking, problem-solving skills, and the ability to communicate complex ideas clearly set outstanding candidates apart. These skills are crucial for advancing AI research, developing innovative solutions, and contributing effectively to academic or industry projects.

What are some common challenges faced by AI PhD researchers in computer science when working on interdisciplinary projects?

AI PhD researchers in computer science often collaborate with experts from fields such as biology, linguistics, or engineering. One common challenge is bridging the gap in terminology and methodology between disciplines, which can slow down project progress. Additionally, integrating diverse datasets and aligning research goals requires strong communication and project management skills. However, overcoming these challenges can lead to innovative solutions and valuable networking opportunities.

What is the difference between Ai Phd Computer Science vs Machine Learning Engineer?

AspectAi Phd Computer ScienceMachine Learning Engineer
Required CredentialsPhD in Computer Science or related field, research experienceBachelor's or Master's in CS, Data Science, or related field, some experience in ML projects
Work EnvironmentResearch labs, academia, R&D departmentsIndustry, tech companies, startups, applied project settings
Employer & Industry UsageUniversities, research institutions, R&D divisions of tech firmsTechnology companies, finance, healthcare, e-commerce
Common Search & Comparison IntentUnderstanding advanced research roles, academic careersPractical application of ML, product development

While an Ai Phd in Computer Science focuses on research, theory, and advancing AI knowledge, a Machine Learning Engineer applies these concepts to develop and deploy ML models in industry settings. Both roles require strong technical skills, but their work environments and career paths differ significantly.

What can you do with a PhD in AI?

A PhD in AI prepares individuals for advanced roles such as AI researcher, data scientist, machine learning engineer, or AI scientist. Graduates often work in research labs, tech companies, or academia, developing algorithms, models, and innovative AI solutions using tools like Python, TensorFlow, or PyTorch.

What are popular job titles related to Ai Phd Computer Science jobs?

For Ai Phd Computer Science jobs, the most frequently searched job titles are:

Infographic showing various Ai Phd Computer Science job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 82% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 81% Physical, 1% Hybrid, and 18% Remote job distribution, with an average salary of $126,612 per year, or $60.9 per hour.

Research Scientist, Generative AI for Physical AI - PhD New College Grad 2026

Santa Clara, CA • On-site

Nvidia Corporation
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidia Corporationexternal

Full-time

Re-posted 3 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies

Job description

Are you passionate about pushing the boundaries of AI at the intersection of the digital and physical worlds? Join our groundbreaking research team as we revolutionize the future of physical AI through groundbreaking generative models. We are now hiring Research Scientists to join our Cosmos team!
As a Research Scientist specializing in Generative AI for Physical AI, you'll be at the forefront of developing next-generation algorithms that bridge the gap between virtual and physical realms. You'll work with state-of-the-art technology and have access to massive computational resources to bring your ideas to life.
What you'll be doing:
  • Pioneer revolutionary generative AI algorithms for physical AI applications, with a focus on advanced video generative models and video-language models
  • Architect and implement sophisticated data processing pipelines that produce premium-quality training data for Generative AI and Physical AI systems
  • Design and develop cutting-edge physics simulation algorithms that enhance Physical AI training
  • Scale and optimize large-scale training systems to efficiently harness the power of 20,000+ GPUs for training foundation models
  • Author influential research papers to share your groundbreaking discoveries with the global AI community
  • Drive innovation through close collaboration with research teams, diverse internal product groups, and external researchers
  • Build lasting impact by facilitating technology transfer and contributing to open-source initiatives

What we need to see:
  • PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
  • Deep expertise in PyTorch and related libraries for Generative AI and Physical AI development
  • Strong foundation in diffusion, vision language and reasoning models and their applications
  • Proven experience with reinforcement learning algorithms and implementations
  • Robust knowledge of physics simulation and its integration with AI systems
  • Demonstrated proficiency in 3D generative models and their applications

Ways to stand out from the crowd:
  • Publications or contributions to major AI conferences (ICLR, NeurIPS, ICML, CVPR, ECCV, SIGGRAPH, ICCV, etc.)
  • Experience with large-scale distributed training systems
  • Background in robotics or physical systems
  • Open-source contributions to prominent AI projects
  • History of successful research-to-product transitions

You'll be part of a team that's defining the future of Physical AI, with access to world-class computing resources and the opportunity to work on problems that matter. Your research won't just live in papers - it will be implemented in real-world systems that push the boundaries of what's possible in AI. Join us in shaping the future of AI where digital intelligence meets physical reality. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous research scientist with a genuine passion for advancing the state of AI? If so, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 14, 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. 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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