Machine Learning Researcher

Next Phase Recruitment; California (MO); On-site; USD 140,000 - 210,000; Full time

Job summary

Next Phase Recruitment is seeking a Machine Learning Research Scientist to advance AI and molecular science, building cutting-edge generative models in a bold, pioneering environment.

You will design diffusion and autoregressive models, develop probabilistic inference and RL methods, collaborate with physics and chemistry experts, and deploy scalable research tools on distributed compute resources.

Strong publication record and expertise in PyTorch or JAX are preferred for this role.

Qualifications

• Advanced degree in Machine Learning, Computer Science, Computational Physics, or related field.
• Industry research experience post-degree
• Strong publication or open-source record in ML research
• Expertise in Python and modern ML frameworks (e.g., PyTorch, JAX)
• Excellent interdisciplinary communication skills

Responsibilities

• Design and train advanced generative models (diffusion, autoregressive, flow-based, latent-variable)
• Develop sampling and simulation methods integrating probabilistic inference and RL
• Bridge simulation and reality through data mapping models
• Rapidly prototype and deploy scalable research tools
• Collaborate with domain experts in physics and chemistry to ground models in real science
• Deep learning and generative architectures
• Probabilistic modeling and Bayesian inference
• Reinforcement learning for molecular systems
• Distributed computing environments

Skills

Deep learning

Probabilistic inference

Reinforcement learning

Interdisciplinary communication

Education

Advanced degree in ML/CS/Physics

Tools

Python

PyTorch

JAX

Job description

Are you passionate about advancing the frontier of AI and molecular science? This is an exciting opportunity for a Machine Learning Research Scientist to develop cutting edge generative models within a bold, pioneering environment. If you have a strong foundation in deep learning, probabilistic inference, and reinforcement learning, and want to shape the next generation of AI for the physical world, this role could be perfect for you.

The Employer

Join a pioneering tech leader at the intersection of AI and chemistry, committed to creating transformative world models for atomic and molecular systems. This well funded and talent dense organization operates on a culture of innovation, rapid execution, and collaboration, with access to immense computing resources and challenges that truly push the boundaries of science and engineering.

Qualifications & Experience

• Advanced degree in Machine Learning, Computer Science, Computational Physics, or related field
• Industry research experience post-degree
• Strong publication or open-source record in ML research
• Expertise in Python and modern ML frameworks (e.g., PyTorch, JAX)
• Excellent interdisciplinary communication skills

Responsibilities

As part of the Machine Learning team, you will:

• Design and train advanced generative models (diffusion, autoregressive, flow-based, latent-variable)
• Develop sampling and simulation methods integrating probabilistic inference and RL
• Bridge simulation and reality through data mapping models
• Rapidly prototype and deploy scalable research tools
• Collaborate with domain experts in physics and chemistry to ground models in real science
• Deep learning and generative architectures
• Probabilistic modeling and Bayesian inference
• Reinforcement learning for molecular systems
• Distributed computing environments

Nice to Haves

• Experience with 3D point clouds and dynamic data
• Probabilistic programming and sequential Monte Carlo methods
• Familiarity with statistical mechanics and computational chemistry
• Multi-cloud and distributed compute systems experience

This is your chance to define the future of AI-driven science in a fast-moving and intellectually stimulating environment.