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Foundation Models Jobs (NOW HIRING)

Autodesk

The Foundation Models team develops AI technologies that operate across Autodesk's platform and business units. This role provides the analytical foundation needed to guide adoption, monetization ...

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How much do foundation models jobs pay per hour?

As of Jun 15, 2026, the average hourly pay for foundation models in the United States is $45.71, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $72.12 per hour, depending on experience, location, and employer.

How do foundation models make money?

Foundation models make money primarily by licensing their technology to companies, providing API access, or offering customized solutions. Organizations may also generate revenue through training, fine-tuning services, or partnerships that leverage these models for specific applications.

What jobs in the US pay 300,000 a year?

In the field of foundation models and AI, senior roles such as AI research directors, machine learning engineers, and data science executives can earn $300,000 or more annually, especially with extensive experience, advanced degrees, and leadership responsibilities. These positions often require expertise in deep learning, large-scale data processing, and proficiency with tools like TensorFlow or PyTorch.

What does a foundation model do?

A foundation model is a large-scale machine learning model trained on diverse data that can be adapted for various tasks such as language understanding, image recognition, or speech processing. In a job context, roles involving foundation models typically require skills in deep learning, data preprocessing, and model fine-tuning using tools like TensorFlow or PyTorch.

What job makes $10,000 a month without a degree?

In the field of foundation models and AI, roles such as AI engineer, machine learning engineer, or data scientist can earn $10,000 or more per month with relevant skills and experience, often without a formal degree if they have strong technical expertise and a portfolio of work. These positions typically require proficiency in programming, deep learning frameworks, and data handling, and may involve working in tech companies or research labs. Salary levels depend on experience, location, and the complexity of projects handled.
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Foundation Models jobs near you
Infographic showing various Foundation Models job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, and 6% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $95,086 per year, or $45.7 per hour.

ML Research Scientist - Atomistic Foundation Models

Achira

New York, NY • On-site

$164K - $259K/yr

Full-time

Posted 23 days ago

Job description

Invent the next generation of deep generative, representational, and simulation models for molecules and materials - building the foundation models that make the atomistic world learnable, predictable, and designable.
Why Achira
  • Join a world-class, interdisciplinary team of ML researchers, physicists, chemists, and engineers reimagining atomistic simulation through large-scale foundation models.
  • Push the frontier where deep learning meets the laws of nature - bridging generative AI, probabilistic reasoning, and molecular physics.
  • Work at a scale few attempt: massive data, massive compute, and massive ambition.
  • Own your research end-to-end - from concept and architecture to training, evaluation, and deployment.
  • Thrive in a culture that rewards rigor, velocity, creativity, and impact - not bureaucracy.
About the Role
Achira is building foundation simulation models - large-scale models that learn the structure, dynamics, and energetics of the atomistic world.
These models unify deep representation learning, generative modeling, and advanced simulation and sampling.
As a Generative AI Researcher, you will:
  • Design and train frontier deep generative models - diffusion, autoregressive, flow-based, and latent-variable architectures - for molecules, materials, and atomic systems.
  • Develop expressive representations of molecular and atomistic structure and dynamics, including equivariant graph neural networks, geometric transformers, and latent encoders that capture physical symmetries and constraints.
  • Invent advanced sampling and simulation methods that integrate probabilistic inference, deep learning, and reinforcement learning - enabling efficient exploration and simulation of learned energy landscapes.
  • Build models that understand, generate, and simulate the physical world - unifying reasoning, simulation, and prediction.
  • Collaborate with physicists and chemists to ground models in ab initio, molecular dynamics, and experimental data.
  • Prototype, benchmark, and iterate rapidly - transforming research ideas into reusable, scalable model components across Achira's foundation model stack.
  • Contribute to publications, open-source tools, and internal research projects that advance the field.
About You
You are a deep learning researcher who moves seamlessly between representation learning, generation, and simulation - motivated by the idea of teaching AI to reason about the physical world.
Required Qualifications
  • PhD or equivalent research experience in machine learning, physics, chemistry, computer science, or a related field.
  • Proven expertise in deep generative modeling (e.g., diffusion, VAEs, flows, autoregressive transformers).
  • Experience in representation learning for structured data, especially graph or 3D geometric models (GNNs, SE(3)/E(3)-equivariant networks, geometric transformers).
  • Proficiency in Python and modern ML frameworks (PyTorch, JAX) plus scientific libraries (NumPy, SciPy).
  • Solid grounding in probability, optimization, and deep learning fundamentals.
  • Demonstrated research impact through publications, open-source contributions, or released models.

Preferred Qualifications
  • Experience with atomistic simulations, molecular dynamics, or electronic-structure data.
  • Familiarity with probabilistic inference, MCMC, variational methods, or reinforcement learning for sampling and control.
  • Experience integrating physics-informed priors or energy-based models into deep architectures.
  • Knowledge of atomistic molecular datasets and benchmarks such as SPICE, OMol25, QCML, AIMNet2
  • Experience scaling models on HPC or distributed GPU infrastructure.
  • Strong technical communication across interdisciplinary teams.

What Success Looks Like
  • You develop models that both represent and generate molecular systems, and simulate their dynamics through learned sampling and reasoning.
  • Your architectures and algorithms become core components of Achira's foundation model platform.
  • You thrive in collaborative interdisciplinary environments.
  • You help define the next era of generative and simulation AI for the physical sciences.

Join Us
At Achira, we're teaching machines to understand and simulate the laws of nature - making matter itself generative, interpretable, and designable.
If you think deeply, build boldly, and dream in equations, tensors, and compute graphs, we want you on our team.
Eligibility
In compliance with United States federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to provide required employment eligibility verification documentation upon hire.

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