Venture Capital Associate - AI Training – Remote

Job Type: Contractor

Location: Remote

Role Description

If you’re a venture capital professional who thrives on market insight, analytical rigor, investment judgment, and clear communication, this is a unique opportunity to contribute directly to how advanced AI systems reason about private markets, startups, and investment decision-making. We’re looking for Venture Capital Associates who can evaluate these concepts with precision. You’ll challenge and evaluate advanced language models on venture capital topics to strengthen model reasoning.

Your Profile

• 4 years of experience in venture capital, growth equity, startup investing, corporate venture capital, investment banking, private equity, or closely related startup finance roles.
• Significant hands-on work with startup diligence, investment memo writing, market mapping, financial analysis, cap table review, or portfolio company analysis.
• Deep knowledge of venture capital deal evaluation, private company valuation, startup business models, fundraising dynamics, term sheets, and investor decision-making.
• Strong understanding of SaaS, marketplace, fintech, AI, consumer, healthcare, enterprise software, or other venture-backed business models and their core operating metrics.
• Proven experience evaluating founders, markets, competitive positioning, unit economics, growth strategy, and investment risk.
• Demonstrated experience in producing clear written analysis for investment committees, partners, founders, board observers, or portfolio stakeholders.
• Bachelor’s degree in finance, economics, business, engineering, data science, or a related field required; MBA, CFA, or equivalent advanced training preferred.
• Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.
  
  

Key Responsibilities

• Evaluate AI-generated responses for technical accuracy, investment logic, market realism, and clarity in venture capital and startup finance contexts.
• Challenge advanced language models with realistic venture capital scenarios involving diligence, valuation, market sizing, business model analysis, and fund-level decision-making.
• Review and refine AI-generated prompts, responses, explanations, investment memos, diligence questions, and financial reasoning.
• Provide structured feedback that identifies reasoning gaps, unsupported assumptions, calculation errors, terminology misuse, and weak investment judgment.
• Shape AI communication standards for how models should explain venture capital concepts to founders, investors, analysts, and business audiences.
• Support benchmarking efforts by creating or reviewing high-quality evaluation tasks that test model performance on VC-specific analytical workflows.
• Assess whether AI outputs appropriately distinguish between early-stage, growth-stage, and late-stage investment considerations.
• Ensure AI-generated content reflects professional standards for concise, evidence-based, and well-structured investment analysis.