Physics and AI specialist

About Turing:

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L

Role Overview:

We are seeking a Data Scientist to design and code complex physics data generation scenarios to evaluate large language model (LLM) agents. The role focuses on stress-testing agent behavior, identifying failure modes, hidden biases, and language-driven differences in model responses, and understanding where current LLM agents fall short.

Responsibilities:

• Design and implement advanced data science scenarios and experiments
• Evaluate LLM agent reasoning, consistency, and robustness 
• Identify subtle failures, bias, and behavior changes driven by language or framing
• Analyze and document where and why agents fail

Required Qualifications:

• Strong background in physics and statistical reasoning
• Excellent coding skills (Python)
• Experience working with or evaluating LLMs

Perks of Freelancing With Turing:

• Work in a fully remote environment.
• Opportunity to work on cutting-edge AI projects with leading LLM companies.
• Potential for contract extension based on performance and project needs.

Offer Details:

• Commitments Required : At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week)
• Engagement type : Contractor assignment/freelancer (no medical/paid leave)
• Duration of contract : 6 months; [expected start date is next week]