ZipRecruiter

Log In

1

Generative Ai Phd Jobs (NOW HIRING)

Cotiviti

Intern - Generative AI/Agentic AI/Research

$32 - $40/hr

... of a PhD. * Demonstrated interest or experience in AI, healthcare technology, or informatics ... Strong foundational knowledge in generative AI model development, architectures, and vector ...

Cotiviti

$32 - $40/hr

... of a PhD. * Demonstrated interest or experience in AI, healthcare technology, or informatics ... Strong foundational knowledge in generative AI model development, architectures, and vector ...

Visa

Head of Generative AI Research

Foster City, CA · Hybrid

As Head of Generative AI Research, you will shape Visa's GenAI research agenda, collaborate with ... Masters, MBA, JD, or MD), PhD with 9+ years of experience. U.S. Applicants Only The estimated ...

N26

Your team develops cutting-edge generative AI workflows, agents, and agentic systems for internal ... An advanced degree (Master's or PhD) in a quantitative discipline such as Computer Science, Data ...

Visa

Head of Generative AI Research

Foster City, CA · On-site

As Head of Generative AI Research, you will shape Visa's GenAI research agenda, collaborate with ... Masters, MBA, JD, or MD), PhD with 9+ years of experience. U.S. Applicants Only The estimated ...

Cotiviti

$32 - $40/hr

Overview The Generative AI Research Engineer Intern conducts primary and secondary research of ... of a PhD. * Demonstrated interest or experience in AI, healthcare technology, or informatics ...

next page

Showing results 1-20

All JobsGenerative Ai Phd Jobs

Generative Ai Phd information

See salary details

$29K

$117.6K

$227.5K

How much do generative ai phd jobs pay per year?

As of Jul 10, 2026, the average yearly pay for generative ai phd in the United States is $117,556.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,000.00 and $169,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Generative AI PhD, and why are they important?

To thrive as a Generative AI PhD, you need deep expertise in machine learning, mathematics, and computer science, typically supported by a doctoral degree in a related field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and experience with large-scale data and cloud computing are essential. Strong research acumen, critical thinking, and the ability to clearly communicate complex ideas are vital soft skills for success in academic or industry settings. These skills drive innovative research, enable effective collaboration, and ensure impactful contributions to the rapidly evolving field of generative AI.

What are some common challenges faced when transitioning from academic research to an industry role as a Generative AI PhD?

One common challenge is adapting to faster-paced project timelines, as industry work often emphasizes practical results and product integration over long-term theoretical exploration. Additionally, collaboration across multidisciplinary teams—including software engineers, product managers, and designers—requires strong communication skills to translate complex research into actionable solutions. Many new hires also find it necessary to balance advancing the state-of-the-art with addressing immediate business needs, which can shift the focus from pure research to more applied problem-solving.

What is a Generative AI PhD?

A Generative AI PhD is a doctoral program focused on researching and developing artificial intelligence systems that can generate new content, such as text, images, music, or code. Students in this program study advanced machine learning techniques, including deep learning, neural networks, and probabilistic models. The goal is to push the boundaries of what AI can create, leading to innovations in fields like natural language processing, computer vision, and creative arts. Graduates often pursue careers in academia, research labs, or tech companies working on cutting-edge AI technologies.

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

AspectGenerative Ai PhdMachine Learning Engineer
Required CredentialsPhD in AI, Computer Science, or related fieldBachelor's or Master's in CS, AI, or related field
Work EnvironmentResearch labs, academia, R&D departmentsTech companies, startups, industry projects
Employer & Industry UsageAcademic institutions, research firms, AI labsTech firms, software companies, AI product teams

Generative Ai Phds focus on advanced research, developing new models and theories in AI, often working in academic or research settings. Machine Learning Engineers implement AI models into products, working in industry environments to develop scalable solutions. While both roles require strong AI knowledge, the PhD emphasizes research depth, whereas the Engineer emphasizes application and deployment.

More about Generative Ai Phd jobs
What cities are hiring for Generative Ai Phd jobs? Cities with the most Generative Ai Phd job openings:
What states have the most Generative Ai Phd jobs? States with the most job openings for Generative Ai Phd jobs include:
What job categories do people searching Generative Ai Phd jobs look for? The top searched job categories for Generative Ai Phd jobs are:
Generative Ai Phd jobs near you
Infographic showing various Generative Ai Phd job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $117,556 per year, or $56.5 per hour.
Research Scientist, Generative AI for Physical AI - PhD New College Grad 2026

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

NVIDIA

Santa Clara, CA • On-site

Full-time

Re-posted 4 hours ago

Job description

Job Summary:
NVIDIA is a leading technology company known for its innovative work in AI. They are seeking a Research Scientist specializing in Generative AI for Physical AI to develop next-generation algorithms and enhance physical AI applications. The role involves pioneering generative AI algorithms, architecting data processing pipelines, and collaborating with various research teams.
Responsibilities:
• 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
Qualifications:
Required:
• 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
Preferred:
• 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
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
Nvidia logo

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

View All Nvidia Jobs

Apply