AI Research Scientist

Salary Range: 100 to 300 (Currency: USD) (Pay period: per-year-salary)

Mission

• Develop scalable MLIP frameworks capable of representing diverse chemical systems with high fidelity.
• Innovate and implement state-of-the-art machine learning models, such as graph neural networks, equivariant architectures, or hybrid approaches for interatomic potential development.
• Curate and integrate large-scale datasets from first-principles calculations (e.g., DFT) and experimental sources.
• Explore active learning and automated data acquisition workflows for efficient dataset expansion.
• Address challenges of scalability, generalizability, and transferability in MLIP designs.
• Optimize training and inference pipelines to leverage high-performance computing resources effectively.
• Contribute to the AI and materials science research community through publications and active engagement in top-tier AI/ML venues like NeurIPS, ICML, ICLR, and our company blog, alongside active participation in conferences and workshops. 
• Tackle challenging problems with new and different ideas, creativity and contrarian thinking.
• Mentor and guide junior team members and interns, promoting an environment of continuous learning and innovation.

About you

• Ph.D., M.S., or B.S. in AI, Machine Learning, Physics, Materials Science, Computer Science, or a closely related field, with a strong focus on atomistic modeling.
• At least 3 years of research experience in AI, especially in graph neural networks, deep learning architectures, or equivariant modeling techniques.
• Solid understanding of materials modeling and interatomic potentials, including DFT and molecular dynamics simulations.
• Familiarity with high-performance computing and distributed training methods.
• Demonstrated experience in designing and running large-scale experiments in AI and machine learning.
• Passionate about leveraging ML for science related problems and a commitment to doing world-class research.
• Proficiency in Python and relevant ML libraries (e.g., PyTorch).
• Strong publication record in top-tier AI/ML conferences or journals.
• Excellent collaboration and communication skills, capable of articulating complex technical ideas clearly and effectively.

Pluses

• Experience in developing or applying MLIPs such as Gemnet, MACE, NequIP, Allegro, or similar frameworks.
• Familiarity with software engineering best practices.

What we offer

• A competitive compensation package also includes the best in benefits:
• Medical, dental, and vision insurance for you and your family
• Mental health and wellness support
• Unlimited PTO and 14+ company holidays per year
• 401K 
• Work closely with a team on the cutting edge of AI research.
• A mission: an opportunity to fundamentally change the way humanity makes progress through materials science discovery.