Member of Technical Staff, Finance Research | $6-$8/hr Remote
Overview
This role sits at the cutting edge where artificial intelligence meets finance. As a Member of Technical Staff on the Finance Research team, you'll design and own the evaluation frameworks that measure how well AI systems handle complex financial tasks—from reasoning and decision-making to full workflow automation. You'll work closely with researchers and engineers to push the boundaries of what AI can do in enterprise finance, turning cutting-edge research into tangible improvements.
What You'll Do9
- 1Create and maintain sophisticated evaluation suites for AI agents operating in finance, including benchmark datasets, scoring rubrics, and rigorous testing protocols.
- 2Conduct original research on financial reasoning and automated decision-making, then translate your findings into measurable upgrades for AI system performance.
- 3Build realistic test environments and curated datasets that mirror the challenges real-world enterprise finance teams face daily.
- 4Partner with AI researchers, ML engineers, and product leads to validate finance-focused models and agentic systems, then refine them based on results.
- 5Analyze model behavior and failure modes to uncover trends and generate actionable recommendations that steer research priorities.
- 6Document your findings in internal research reports and technical guides that help the organization understand AI's evolving role in finance.
- 7Keep up with the latest advances in machine learning, financial modeling, and agent architectures, and integrate promising techniques into your work.
- 8Help establish micro1 as a thought leader in enterprise financial intelligence and AI evaluation by setting high standards for research quality.
- 9Foster a culture of scientific rigor and collaborative innovation across a remote, distributed research team.
Requirements7
- 1Advanced degree in Finance, Economics, Financial Engineering, Quantitative Finance, or a closely related field (PhD strongly preferred; an MBA, CFA, or equivalent expertise is also welcomed).
- 2Deep knowledge of at least one finance domain—such as investment research, capital markets, risk management, corporate finance, accounting, or financial analysis.
- 3Proven experience in designing rigorous research methodologies or evaluation frameworks in finance or another quantitative discipline.
- 4Ability to turn vague, real-world finance problems into clear, measurable research questions and evaluation criteria.
- 5Strong analytical and critical-thinking skills, with a track record of tackling complex, cross-disciplinary challenges.
- 6Excellent written and verbal communication skills, especially for creating research reports, technical documentation, or thought leadership content.
- 7Experience thriving in cross-functional teams where research, engineering, and product stakeholders collaborate closely.
Who Should Apply
We're looking for someone who lives at the intersection of deep finance expertise and AI research. You're equally comfortable debating the nuances of a risk model and designing an evaluation benchmark for an LLM-based trading agent. You enjoy turning ambiguous problems into structured research experiments and have a passion for advancing how AI understands and handles financial data. If you have a PhD in a quantitative field and experience with AI evaluation or agentic systems, you'll be a great fit.
Salary Insight
The base salary for this full-time remote role is $200,000–$250,000. All employees are eligible for equity and may receive performance-based bonuses. The company also offers up to 100% reimbursement for health-insurance premiums, paid time off, a 401(K) with company match, and other benefits designed for a remote-first team.
Location
Required Skills
Application Tip
In your cover letter or application, highlight a specific project where you built an evaluation framework or benchmark—preferably one that involved both financial domain knowledge and AI systems. Show how your methodology improved performance or uncovered key failure modes.
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