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Still Model Jobs (NOW HIRING)

Adecco

Scan Model

Nashville, TN

$50/hr

Follow all scan model safety protocols and screening requirements as instructed ... Remain still during imaging procedures to ensure high-quality scans. * Communicate any discomfort ...

New

Adecco

MRI Scan Model

Cleveland, OH · On-site

$35/hr

Job Summary The MRI Scan Model participates in MRI imaging sessions to support equipment ... Remain still during imaging procedures to ensure high-quality scans. * Communicate any discomfort ...

Model N

Regional Sales Manager, New Business Sales

$150K - $170K/yr

... still encourage you to apply. We value diverse experiences, curiosity, and people who are excited to grow. At Model N, your well-being and growth matter. That's why we offer a robust total rewards ...

Haas F1 Team

Senior Model Maker

Independence, KY · On-site

Ten years later, the team is still building momentum, guided by clear objectives and technical ... General Summary This role reports to the Team Leader Model Maker or their designee and is based in ...

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How much do still model jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for still model in the United States is $31.37, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $39.18 per hour, depending on experience, location, and employer.

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Infographic showing various Still Model job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $65,246 per year, or $31.4 per hour.

Member of Technical Staff - Machine Learning Capabilities

Seattle, WA • On-site

Preference Model
See more jobs at Preference Modelexternal

$200K - $350K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 29 days ago

Key responsibilities

  • Design and build reinforcement learning environments and reward functions for ML research and engineering tasks

  • Conduct experiments, evaluations, and deliver environments into production training runs

  • Collaborate with researchers and engineers to brainstorm and create new ideas and tools for environment building

Job description

About Us
Preference Model is building automated ML research engineering.
Existing frontier models are brittle when applied to real-world ML tasks. The present bottleneck is the lack of high-quality RL training environments. Our first step is to build RL environments that reflect real-world complexity, with diverse tasks and robust reward functions.
Our founding team has previous experience on Anthropic's data team building data infrastructure, and datasets behind Claude. We are partnering with leading AI labs to push AI closer to achieving its transformative potential.
About the Role
We're hiring experienced Machine Learning Engineers to design and build reinforcement learning environments to safely advance model capabilities in machine learning research and engineering. Specifically, you'll be teaching frontier models to do the work of an ML engineer or researcher at a frontier lab.
This role blends research and engineering. It will require you to stay up to date with the latest research, develop novel approaches, and realize them in code. You will have full ownership and autonomy of the environments you build. Your work will include designing and implementing RL environments, conducting experiments and evaluations, delivering your work into production training runs, and collaborating with other researchers and engineers.
You will join our Capabilities org, a small, high-ownership team and contribute directly to the data layer that powers frontier LLM capability.
Note: This role is only for experienced ML Engineers. We have a separate opening for New Grads.
What You Will Do:
  • Design and build RL environments and reward functions that produce clean, learnable signals for frontier models on ML research and engineering tasks
  • Build deep expertise across the frontier of ML research, training, and inference infrastructure
  • Collaborate with others to brainstorm and create new ideas and tools to improve the environment building process
What We are Looking For (Qualifications):
  • 5+ years of experience working in machine learning or research, primarily on LLMs and transformer models
  • You have strong ML fundamentals and broad research interests. You read many papers or tutorials, understand topics deeply and have the creativity to translate them into RLVR problems
  • Proficiency in Python and systems programming and at least one of PyTorch or JAX
  • Problem solvers who take ownership and drives solutions end-to-end
  • Passion for staying current with the rapidly evolving ML infrastructure landscape
  • Ability to meet throughput expectations and respond quickly to feedback
You may be a good fit if you also:
  • Have expert knowledge in an active DL/ML research area, with publications or public code to show for it. Research experience (PhD, MS) is a big plus
  • Have deep understanding of transformer internals, training/inference of modern LLMs, experience with inference libraries (vLLM, SGLang, etc)
  • Have strong expertise in kernel development (CUDA, Triton, Pallas)
  • Have built complex interactive RL environments
What We Offer:
  • Competitive cash and equity compensation (>90th percentile)
  • Ownership and autonomy in a fast moving startup environment
  • Opportunity to work with top machine learning engineers
  • Health, vision, dental, benefits
  • 401K match
  • Lunch provided everyday onsite
  • Weekly snack orders
  • Visa sponsorship & relocation support available

We value diverse perspectives and experiences. If you're excited about this role but don't check every box, we still encourage you to apply.

Apply