Role Description Join a leading AI lab’s cutting-edge Generative AI team and play a pivotal role in building next-generation large language models. We are seeking experienced Operations professionals to contribute deep domain expertise and enhance the quality of AI training data. In this role, you will work closely with research teams to design, evaluate, and refine operational problem sets, helping AI systems better understand and solve complex, real-world business challenges. What You’ll Do - Partner with research teams to identify and close knowledge gaps in Operations-related domains - Design complex, real-world tasks across various operations specializations and develop structured, high-quality solutions - Evaluate operational scenarios and solutions, providing clear, actionable feedback - Contribute to improving AI model performance through domain expertise - Collaborate with other subject matter experts to ensure consistency, accuracy, and quality of training data Qualifications - 8+ years of professional experience in Operations, with a strong track record in leadership roles - Demonstrated career progression into senior operations positions (e.g., Operations Manager, Director of Operations, VP of Operations, or similar) - Experience working in recognized enterprises, high-growth companies, or consulting environments - Strong analytical, problem-solving, and decision-making skills - Excellent written and verbal communication abilities Requirements - W-2 employment structure with placement at a leading AI lab as part of an extended workforce - Minimum commitment of 20 hours per week during weekdays - Opportunity to work on high-impact AI initiatives in a collaborative environment Benefits - Be at the forefront of AI innovation and model development - Apply real-world operations expertise to shape how AI understands business processes - Collaborate with top-tier professionals across technology and research domains Additional Information - This role involves contributing to AI training and evaluation workflows in a structured environment - Responsibilities and scope may evolve based on project needs and performance Equal Opportunity Statement All qualified applicants will be considered without regard to legally protected characteristics. Reasonable accommodations are available upon request.

• Design advanced computational problems requiring the use of domain-specific scientific software • Create tasks that test both precise execution (multi-step workflows, simulations) and strategic reasoning (experiment design, inference from partial data) • Develop problem setups, solution pathways, and validation mechanisms • Calibrate and refine tasks based on model performance to achieve target difficulty levels • Ensure problems emphasize reasoning strategy over brute-force computation

• Review and assess financial and investment-related content, including equity research, models, and market analyses • Contribute to the development and refinement of high-quality analytical materials • Apply long/short equity frameworks to evaluate valuation, earnings performance, and market positioning • Provide structured, actionable feedback to improve clarity, rigor, and accuracy • Support tasks involving earnings forecasting, investment memos, and research summaries

• Design clinically accurate and realistic case scenarios based on your specialty, including diagnostic reasoning, treatment planning, risk stratification, and guideline-based care • Develop “gold standard” responses at an attending-physician level to guide AI model learning • Evaluate and grade AI-generated outputs using structured rubrics and evidence-based medical standards • Provide detailed written feedback to enhance model accuracy, safety, and clinical reasoning • Participate in onboarding sessions, office hours, and specialty-specific calibration discussions