Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Evaluate finance workflows and tasks for realism, technical accuracy, and practical applicability in trading, derivatives, and crypto markets. Identify ambiguous assumptions, unrealistic constraints, missing edge cases, and provide concise, actionable feedback. Collaborate with domain experts to maintain consistency and ensure high-quality assessments throughout a fast-paced, remote sprint engagement.

Evaluate AI-generated JSON outputs using detailed grading rubrics. Read and parse structured data, apply rubric-based scores consistently, identify discrepancies or missing information, and produce evidence-based justifications while meeting turnaround requirements and working independently without AI-assisted tools.

Provide insurance subject-matter expertise to improve generative AI models: design insurance tasks, create reference solutions, evaluate AI outputs with structured rubrics, refine scoring guidelines, and collaborate with research and engineering teams to produce high-quality training and evaluation data. Commitment of 35+ hours/week and proven senior insurance experience required.

Review, create, and evaluate professional operational finance deliverables (P&L reconciliations, month-end close, AP/P2P, three-statement models, pro forma analysis, covenant and partnership accounting). Analyze complex documents, assess AI-generated financial work for technical accuracy and completeness, and produce executive-ready summaries with assumptions, variances, impacts, and recommendations.

Evaluate and review AI-generated mechanical engineering content for technical accuracy and real-world applicability; provide expert answers and feedback; recommend standards and references; share design, manufacturing, and testing insights; identify errors and collaborate with subject-matter experts to improve AI model quality. Part-time, remote, contractor (~10 hrs/week).

Part-time remote role reviewing and improving AI-generated electrical engineering content. Provide expert answers, identify technical inaccuracies, recommend standards/resources, and share practical engineering workflows and documentation to improve AI model quality.

Design evaluation rubrics and scoring frameworks for marketing deliverables, assess AI-generated and human-created marketing work with evidence-based judgments, provide written justifications, and iterate with stakeholders to improve consistency and scoring quality.

Design task-specific grading criteria for B2B sales deliverables and evaluate AI-generated and human work against those rubrics. Provide detailed, evidence-based written justifications, refine rubrics with senior reviewers, and ensure consistent, reproducible evaluations across large volumes of work.

Review and evaluate quantitative finance tasks for technical accuracy and real-world realism. Identify missing assumptions, unrealistic constraints, edge cases, and data or backtesting issues. Provide concise, structured written feedback and actionable recommendations. Collaborate with other experts to calibrate evaluations and maintain consistent quality standards throughout a high-engagement, remote contractor sprint.

Design realistic, multi-step data analysis benchmark tasks and create reproducible reference analyses. Evaluate AI-generated analyses for correctness, statistical validity, and interpretation. Collaborate with researchers to improve benchmark quality and document methodologies in Jupyter/Colab notebooks.