ZipRecruiter

Log In

1

Diffusion Model New Jobs (NOW HIRING)

Extropic

Research Scientist - Machine Learning

Boston, MA · On-site

$150K - $250K/yr

Collaborate with senior researchers, residents, engineers, and physicists to derive the theory of new probabilistic models and their learning rules, including energy-based models and diffusion models.

Magna

Robotics AI Algorithm- R&D Summer 2026

Troy, MI · On-site

... NLP), Diffusion models, Gen-AI). • Create representative case study to understand solution ... new Deep Learning architectures. • Prior experience with model training and inference. • ...

Genesis Molecular AI

Senior CADD Scientist

San Diego, CA · On-site +1

$97K - $132K/yr

... models for molecular AI to unlock a new era of drug design and development. The company ... diffusion model Pearl for structure prediction. Genesis has raised over $300 million from leading ...

Apex Informatics

Applied Machine Learning Engineer

Familiarity with GenAI architectures like transformers, LLMs, or diffusion models. * Proactive nature, ability to creatively solve problems you face and bring new ideas to the team. * Clear and ...

Purple Drive

GEN AI Engineer

Chicago, IL · On-site

... new techniques. Required Skills & Experience * 5-8 years of Python development experience. * Hands-on expertise in Generative AI, LLMs, Transformers, or Diffusion Models . * Strong background in ...

Purple Drive Technologies

GEN AI Engineer

Chicago, IL · On-site

... new techniques. Required Skills & Experience * 5-8 years of Python development experience. * Hands-on expertise in Generative AI, LLMs, Transformers, or Diffusion Models . * Strong background in ...

next page

Showing results 1-20

People also search for

All JobsDiffusion Model New Jobs

Diffusion Model New information

See salary details

$30

$52

$96

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 - Machine Learning

Extropic

Boston, MA • On-site

$150K - $250K/yr

Full-time

Posted 9 days ago

Job description

Overview
Extropic's hardware massively accelerates certain kinds of probabilistic inference.  Our ML team works on the science of training models in the thermodynamic paradigm, and we are looking for senior research and engineering talent to derive probabilistic ML theory, empirically demonstrate its scaling properties, and deploy performant models. Senior hires will be leading their own research direction and are therefore expected to quickly become experts across our abstraction stack, including the hardware, software, physics, and math.
Responsibilities
  • Collaborate with senior researchers, residents, engineers, and physicists to derive the theory of new probabilistic models and their learning rules, including energy-based models and diffusion models.
  • Scale up experimentation infrastructure and optimize over the design space of models.
  • Implement, visualize, and evaluate new architectures, training algorithms, and benchmarks.
  • Publish papers, contribute to open source, and communicate design insights to our hardware team.
  • Create production models for domain experts using customer data.
Required Qualifications
  • Experience in scientific Python and at least one deep learning framework (PyTorch, JAX, TensorFlow, Keras)
  • Extremely strong foundations in probability and linear algebra
  • Familiarity with deep learning theory and literature, including theory of over-parameterization and scaling laws
  • Publications in top ML conferences (NeurIPS, ICML, ICLR, CVPR)
  • Experience training high-performance models, including familiarity with infrastructure (Slurm, Ray, Weights & Biases)
  • Experience deploying models, including familiarity with infrastructure (Ray, AWS, ONNX)
Preferred Qualifications
  • Experience designing probabilistic graphical models (PGM)
  • Experience training energy-based models (EBMs) or diffusion models
  • Experience with numerical methods in diffeq solvers
  • Experience with message passing or training graph neural networks (GNNs)
  • Strong theoretical background in information geometry
  • Strong theoretical background in random matrix theory
  • Strong grasp of computational Bayesian methods, including MCMC sampling methods and variational inference
$150,000 - $250,000 a year
Salary and equity compensation will vary with experience
 
Extropic is an equal opportunity employer
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
apply for this job

Apply