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Diffusion Model Jobs (NOW HIRING)

AI Engineer

San Francisco, CA ยท On-site +1

$145K - $198K/yr

With diffusion models driving innovation in 2D and 3D, and large language models (LLMs) simplifying workflows, we're creating tools that feel intuitive, adaptable, and powerful. The Role As an AI ...

You will work with large language models (LLMs), diffusion models, and transformer-based architectures to build intelligent, creative, and scalable AI systems.Key Responsibilities * Design, fine-tune ...

Senior Applied Scientist, ASCS AI Lab Team

Seattle, WA ยท 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 ยท 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 Jun 5, 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 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 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 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 May 2026, with employment types broken down into 83% Full Time, 13% Part Time, 1% Temporary, and 3% 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.

AI Engineer

Vizcom Technologies, Inc.

San Francisco, CA โ€ข On-site, Remote

$145K - $198K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 29 days ago


Job description

About Us
At Vizcom, we believe design is one of the most powerful ways to shape the world. Designers at companies like Nike, General Motors, and Riot Games rely on our tools to bring their ideas to life, moving from concepts to reality with clarity and speed.
We're building AI systems that make creativity easier and more natural. With diffusion models driving innovation in 2D and 3D, and large language models (LLMs) simplifying workflows, we're creating tools that feel intuitive, adaptable, and powerful.
The Role
As an AI Engineer, you'll develop systems that redefine how designers work, removing barriers between ideas and execution. This role is about building tools that make AI feel like a natural part of the creative process.
You'll:
  • Expand Diffusion Models: Advance systems for generating, refining, and enhancing content in 2D and 3D.
  • Bring 3D into Focus: Use diffusion models to generate shapes and materials, ensuring outputs are consistent and useful for real-world design.
  • Create Intelligent Agents: Build LLM-powered tools that help designers by automating repetitive tasks and providing thoughtful feedback.
  • Optimize for Designers: Adapt AI systems to be fast, reliable, and easy to use in real-time workflows.
  • Build for Integration: Ensure that 2D and 3D tools work together seamlessly, helping designers move easily between different types of projects.

What We Value
At Vizcom, we care about building tools that are useful, reliable, and simple to use.
  • Expertise in Diffusion Models: You have experience working with 2D and 3D diffusion techniques, and you're eager to push them further.
  • Understanding of 3D Systems: You know how to handle 3D data and use AI to make it more accessible and practical.
  • Practical AI Knowledge: You're familiar with LLMs and can apply them to solve real problems for users.
  • Focus on Performance: You make systems that are efficient, scalable, and robust.
  • Empathy for Designers: You build tools with the people using them in mind, ensuring that AI enhances their work rather than complicating it.

Our Tech Stack
  • AI Frameworks: PyTorch, Hugging Face Diffusers, TensorFlow, and custom implementations of diffusion models.
  • Generative Systems: 2D and 3D diffusion for image creation, material synthesis, and multi-view workflows.
  • LLM Integration: GPT-based agents for task automation and creative support.
  • Infrastructure: Kubernetes, CUDA, and GPU clusters optimized for training and real-time inference.
  • Data Pipelines: Tools for dataset preparation, augmentation, and continuous improvement in 2D and 3D contexts.

Why This Matters
Design shapes how the future takes form. Your work will help designers create products that improve lives, from cars to games to wearable tech. The systems you build will make their work faster, easier, and better, giving them more time to focus on the ideas that matter most.
If you're ready to take on meaningful challenges and build tools that will directly impact how the world is designed, we want to hear from you.
Benefits (for U.S. W2 Employees)
  • Full medical coverage for you, 25% for dependents
  • Dental & Vision insurance
  • Company equity
  • Flexible time off
  • Work from anywhere
  • 401(k) with company match
Compensation:
The base pay range targeted for this position is: $145,000 - $198,000. This role is eligible for equity.
The actual offer, including the compensation package, is determined based on multiple factors, including experience, location, and other business considerations. The overall package described in this post applies to W2, U.S. based employees- final package will be determined by local requirements and employment laws and accessibility.
*Please note, as part of our SOC2 Type 2 compliance, all employees are required to submit to a background check
Join Us and Make an Impact:
At Vizcom, we move fast, offer meaningful equity ownership, and provide a compelling growth trajectory for our team members. We believe in the art of industrial design and strive to improve our world through accelerated visionary processes. Join us in shaping a world designed by you.