AMO Physicist for AI Model Training

Apply advanced expertise in atomic, molecular, and optical physics to a specialized project focused on atomic structure, polarizability, and the optical properties of materials. This part-time contractor role supports the development and evaluation of next-generation AI systems through technically rigorous scientific input. Prior AI experience is not required.

• Provide expert insight on atomic, molecular, and optical physics, with particular emphasis on the optical properties of materials.
• Review, analyze, and discuss ab initio configuration interaction methods used to calculate polarizability in atomic systems.
• Provide guidance and technical critique on atomic-structure calculations involving Yb-171 and Yb-174 isotopes.
• Identify and distinguish sigma and pi transitions in relevant atomic spectra, including explanation of the underlying physical principles.
• Contribute domain expertise that helps train and evaluate advanced AI systems.
• Participate in adaptive spoken AI interviews, answering one question at a time and providing clear examples drawn from research or project work that can legally be shared.

• Advanced degree, including an MS, PhD, or equivalent experience, in Physics with a focus on AMO physics, optical properties of materials, or a closely related area.
• Experience with ab initio quantum calculations, particularly configuration interaction approaches used for polarizability.
• Strong understanding of atomic-structure computational techniques, especially as applied to ytterbium isotopes Yb-171 and Yb-174.
• Ability to identify and explain sigma versus pi transitions in atomic contexts.
• Strong written and verbal scientific communication skills, with the ability to present technical concepts clearly and in a structured way.

• Part-time independent contractor engagement.
• Fully remote and open to candidates worldwide.
• Expected commitment of 5 to 10 or more hours per week.
• Scheduling is fully flexible, including the option to work after hours or on weekends if needed.

Compensation ranges from $100 to $200 per hour.

Candidates apply electronically and must acknowledge the applicable candidate terms and privacy policy as part of continuing through the application process.