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Diffusion Model Jobs (NOW HIRING)

... models • Experience on diffusion model optimization, neural network pruning/knowledge distillation/quantization/architecture search, sub-quadratic attention optimization, efficient architecture ...

Senior Applied Scientist, ASCS AI Lab Team

Seattle, WA · On-site

$104K - $142K/yr

We are seeking a Senior Applied Scientist to join our team in developing pioneering AI research, Generative AI, Agentic AI, Large Language Models (LLMs), Diffusion and Flow Models, and other advanced ...

Senior Applied Scientist, ASCS AI Lab Team

Seattle, WA · On-site

$104K - $142K/yr

We are seeking a Senior Applied Scientist to join our team in developing pioneering AI research, Generative AI, Agentic AI, Large Language Models (LLMs), Diffusion and Flow Models, and other advanced ...

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Diffusion Model information

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$30

$52

$96

How much do diffusion model jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for diffusion model 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 diffusion models in machine learning?

Diffusion models are a type of generative model in machine learning that create data, such as images, by simulating a process where noise is gradually removed from a random signal. These models learn to reverse a diffusion process, transforming noisy data into structured outputs that resemble real examples from the training set. They have gained popularity for producing high-quality, realistic images and other media. Diffusion models are used in various applications, including image synthesis, inpainting, and audio generation.

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 a strong background in machine learning, deep learning, mathematics, and programming, usually supported by a degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, experience with large-scale data processing, and knowledge of diffusion model architectures are typically required. Creativity, problem-solving, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and advancing research. These skills enable the development and implementation of cutting-edge generative models that drive innovation in AI applications.

What are some common challenges faced by professionals working with diffusion models, and how can these be addressed?

Professionals working with diffusion models often encounter challenges related to computational resource demands, model stability, and data quality. Training large diffusion models can require significant GPU resources and careful tuning to prevent issues like mode collapse or slow convergence. Collaborating closely with data engineers and domain experts helps ensure high-quality, diverse datasets, which are critical for realistic outputs. Staying up-to-date with the latest research and best practices can also help address these challenges and advance your skills in this rapidly evolving field.

What is the difference between Diffusion Model vs Data Scientist?

AspectDiffusion ModelData Scientist
Required CredentialsTypically a background in machine learning, statistics, or computer scienceDegree in data science, statistics, computer science, or related fields
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness, tech firms, consulting, research institutions
Industry UsageUsed in AI image generation, generative modelingAnalyzing data, building predictive models, data visualization

While both roles involve data and algorithms, a Diffusion Model focuses on developing generative AI models, whereas a Data Scientist analyzes data to inform business decisions. Understanding these differences helps in choosing the right career path or job focus.

Infographic showing various Diffusion Model job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $108,534 per year, or $52.2 per hour.

Research Engineer

Seattle, WA • On-site

Adobe
Computer and Computer Peripheral Equipment and Software Wholesalers • 10K+ employees

Full-time

Re-posted 23 days ago


Adobe rating

8.9

Company rating: 8.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

38th of 247 rated software companies


Job description

Job Summary:
Adobe is a company that empowers everyone to create through innovative platforms and tools. They are seeking a Research Engineer to develop high-performance ML models, focusing on optimizing resource consumption for large-scale generative models in cloud and on-device deployments.
Responsibilities:
• Play a key collaborative role in ambitious research projects
• Be valued as a specialist in your domain of expertise
• Build innovative tool that enables users to explore their creative potential
• Contribute to existing Adobe tools as well as completely new applications
• Impact products that are used by tens of millions of people
• Learn from your peers and grow into new opportunities
Qualifications:
Required:
• Passion for model optimization/compression and high-performance computing
• Solid deep learning skills, including practical experience in computer vision/natural language processing
• Knowledgeable about the current state of the art in ML efficiency
• Experience in improving the efficiency of mid- to large-scale ML models
• Software engineering expertise
• Proficiency with Python and ML libraries like PyTorch, TensorFlow, JAX, or similar
• Strong communication and collaboration skills
• Ph.D. /Master's degree in Computer Science or a related field, or 3 years of industry experience
Preferred:
• Knowledge of state-of-the-art machine learning methods for large scale multimodal models
• Experience on diffusion model optimization, neural network pruning/knowledge distillation/quantization/architecture search, sub-quadratic attention optimization, efficient architecture design and on-device ML
• Experience with sparse mixture of experts and related techniques
• Experience running ML models within a deployment environment (using TensorRT, AITemplate, CoreML, WinML, TensorFlow Lite, ONNXRuntime or similar)
• Hands-on experience in designing ML models between different platforms (Cloud, mobile, in-browser, etc.)
• Knowledge of design techniques for mobile-friendly ML models
• Proficiency with C++
Company:
Adobe is a software company that provides its users with digital marketing and media solutions. Founded in 1982, the company is headquartered in San Jose, USA, with a team of 10001+ employees. The company is currently Late Stage.

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About Adobe

Sourced by ZipRecruiter

Adobe for All is our vision to advance diversity, equity, and inclusion (DEI) across our company and in our communities. We’re focused on creating a more diverse and inclusive workforce; unleashing the full potential of every employee; and driving meaningful impact for Adobe, our industry, and society at large. Creativity has the power to unite us and inspire us to change the world. Through a vision we call Creativity for All, we’re empowering millions of people of all ages and backgrounds to express themselves, reach their full potential, and share their diverse perspectives with the world. We’re committed to advancing the responsible use of technology and driving a positive environmental impact through sustainability and climate action. Our innovations are making a significant impact across AI ethics, security, privacy, trust and safety, accessibility, and sustainability.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1982