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Diffusion Model New Jobs (NOW HIRING)

Design and conduct rigorous experiments to validate new ideas and evaluate model performance ... particularly diffusion models * Extensive experience implementing and optimizing large-scale ...

Design and conduct rigorous experiments to validate new ideas and evaluate model performance ... particularly diffusion models * Extensive experience implementing and optimizing large-scale ...

Real-time Video Researcher

Palo Alto, CA ยท On-site

$185K - $400K/yr

Work on diffusion model distillation and develop diffusion-based world models for video ... Stay at the cutting-edge of the field, monitoring new developments in real-time video, generative ...

Research Engineer

New York, NY ยท On-site

$200K - $300K/yr

To do this we're developing cutting-edge diffusion models and designing novel, personalized ... Are self-driven, high-agency, and can learn new things quickly and deeply * Have implemented ML ...

Gen AI Engineer Full time job Indianapolis/Dallas, TX/Chicago/SFO/ New York About the Role We are ... You will work with large language models (LLMs), diffusion models, and transformer-based ...

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Diffusion Model New information

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How much do diffusion model new jobs pay per hour?

As of Jun 4, 2026, the average hourly pay for diffusion model new in the United States is $52.18, according to ZipRecruiter salary data. Most workers in this role earn between $38.46 and $96.15 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Diffusion Model Engineer, and why are they important?

To thrive as a Diffusion Model Engineer, you need strong expertise in machine learning, deep learning, and mathematics, typically supported by a degree in computer science or a related field. Experience with frameworks like PyTorch or TensorFlow, familiarity with diffusion model architectures, and knowledge of cloud computing platforms are essential technical qualifications. Creativity, problem-solving, and strong collaboration skills help you design novel models and work effectively in research or product teams. These competencies are crucial for developing state-of-the-art generative models that advance AI capabilities and meet organizational goals.

What are the typical collaboration points between a Diffusion Model Engineer and other teams within a machine learning organization?

Diffusion Model Engineers frequently collaborate with data scientists, research scientists, and software engineers to develop, optimize, and deploy generative models. They work closely with data teams to ensure high-quality, diverse datasets for training, and may partner with product or design teams to align model outputs with user needs. Regular cross-functional meetings and code reviews help ensure alignment on model objectives, deployment standards, and ethical considerations, making strong communication skills essential. This collaborative environment supports continuous learning and innovation, providing ample opportunities for professional growth and specialization.

What are Diffusion Model New jobs?

Diffusion Model New jobs refer to roles that focus on the development, application, and optimization of the latest diffusion models in machine learning and artificial intelligence. These positions typically involve research and engineering tasks related to generative AI, where diffusion models are used to create realistic images, text, or other data types. Professionals in this field work on innovating model architectures, improving training efficiency, and applying these models to real-world problems such as image synthesis, natural language processing, and beyond. The job may also require collaboration with multidisciplinary teams to deploy diffusion model solutions in industry or academia.

What is the difference between Diffusion Model New vs Data Scientist?

AspectDiffusion Model NewData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or related fieldsDegree in Computer Science, Statistics, or related fields
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness, tech firms, research institutions
Industry UsageAI research, generative models, machine learning applicationsData analysis, predictive modeling, business insights

Diffusion Model New focuses on developing and refining generative AI models, often requiring advanced AI expertise. Data Scientists analyze data to extract insights and build predictive models. While both roles involve data and algorithms, Diffusion Model New is more specialized in AI research and model creation, whereas Data Scientists work across broader data analysis tasks.

Infographic showing various Diffusion Model New job openings in the United States as of May 2026, with employment types broken down into 5% Locum Tenens, 1% Full Time, 35% Part Time, and 59% Contract. Highlights an 79% Physical, 1% Hybrid, and 20% Remote job distribution, with an average salary of $108,534 per year, or $52.2 per hour.

Research Scientist (diffusion)

Genmo

San Francisco, CA โ€ข On-site

Full-time

Posted 20 days ago


Job description

We are Genmo, a research lab dedicated to building open, state-of-the-art models for video generation towards unlocking the right brain of AGI. Join us in shaping the future of AI and pushing the boundaries of what's possible in video generation.
Role overview:
We are seeking an exceptional Research Scientist to join our team, focusing on developing cutting-edge diffusion models for text-to-video generation. In this role, you will be at the forefront of innovation, creating novel architectures and algorithms that transform written descriptions into stunning, coherent video content.
Key responsibilities:
  • Lead research initiatives in advanced diffusion models for text-to-video generation, focusing on improving visual quality, temporal consistency, and semantic fidelity
  • Develop and implement state-of-the-art algorithms for translating textual descriptions into dynamic video content
  • Design and conduct rigorous experiments to validate new ideas and evaluate model performance
  • Collaborate with cross-functional teams to integrate research breakthroughs into our production pipeline
  • Stay at the cutting edge of the field by regularly reviewing academic literature and attending top-tier conferences
  • Contribute to the research community through high-quality publications and open-source contributions
  • Mentor junior researchers and foster a culture of innovation within the research team
  • Work closely with product teams to align research directions with user needs and market opportunities

Qualifications:
  • Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field
  • Must have:
    • Strong publication record in top-tier conferences (e.g., CVPR, ICCV, NeurIPS, ICML) with a focus on generative models, particularly diffusion models
    • Extensive experience implementing and optimizing large-scale generative models for image or video tasks
    • Deep understanding of state-of-the-art techniques in text-to-image and text-to-video generation
    • Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
    • Excellent communication skills with the ability to explain complex technical concepts to diverse audiences
    • Proven ability to work collaboratively in a team environment
  • Ideal candidate will have:
    • Postdoctoral or industrial research experience in generative AI for video
    • Hands-on experience with text-to-video generation projects
    • Expertise in other generative model architectures (e.g., GANs, VAEs) and their applications to video
    • Experience working with large-scale datasets and distributed computing environments
    • Track record of successful collaboration with product teams on technology transfers
    • Familiarity with video codecs, compression techniques, and perceptual quality metrics
    • Contributions to open-source projects in the field of generative AI

Additional information
The role is based in the Bay Area (San Francisco). Candidates are expected to be located near the Bay Area or open to relocation.
Genmo is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law. Genmo, Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish.