Financial AI Researcher (Remote)

Joblet-AI; India; Remote; INR 18,815,000 - 23,518,000; Full time

Benefits offered by this job

Equity compensation

Performance bonuses

Health insurance reimbursement

401(k) with company match

Job summary

micro1 is seeking a highly qualified Member of Technical Staff, Finance Research, to advance AI-powered financial reasoning in a remote setting. You will define and evolve evaluation frameworks for AI agents operating in financial domains, and collaborate with researchers, engineers, and product teams to improve finance-focused models.

You will conduct original research on financial reasoning and workflow automation, develop datasets and benchmarks, and publish insights to guide enterprise AI

Qualifications

• Advanced research mindset with focus on finance or quantitative disciplines.
• Ability to translate complex financial problems into measurable research questions.
• Experience designing and evaluating AI systems in finance.

Responsibilities

• Design, own, and evolve evaluation frameworks for AI agents in finance, including benchmarks and scoring methodologies.
• Conduct original research on financial reasoning and workflow automation to improve AI performance.
• Develop and curate datasets, test cases, and benchmark environments reflecting enterprise finance challenges.
• Collaborate with researchers, engineers, and product teams to evaluate finance-focused models and agentic systems.
• Analyze model behavior and performance trends to derive actionable insights.
• Publish internal research findings and best practices for enterprise finance AI.
• Stay current with advances in AI, ML, and financial modeling.
• Help establish research standards and thought leadership for enterprise financial intelligence.
• Foster a culture of scientific rigor and collaborative innovation.

Skills

Analytical thinking

Communication skills

Cross-functional collaboration

Problem solving

Education

PhD strongly preferred in Finance/Quantitative field

MBA or CFA or equivalent expertise

Tools

Python

SQL

ML frameworks

Job description

• Role Title: Member of Technical Staff, Finance Research
• Role Type: Full-time
• Location: Remote

The Role

Join our research team as a Member of Technical Staff (MTS), Finance Research, where you'll help define the frontier of AI-powered financial reasoning. This role sits at the intersection of large language models, agentic systems, and enterprise finance, with a focus on building rigorous evaluation frameworks that measure, benchmark, and advance AI performance across complex financial workflows.

You will conduct applied research, develop novel methodologies for assessing financial intelligence in AI systems, and partner closely with researchers, engineers, and product teams to shape the next generation of enterprise AI.

What You'll Be Doing

• 1. Design, own, and evolve evaluation frameworks for AI agents operating in financial domains, including benchmark suites, scoring methodologies, quality rubrics, and research-grade evaluation protocols.
• 2. Conduct original research on financial reasoning, decision-making, and workflow automation, translating findings into measurable improvements in AI system performance.
• 3. Develop and curate datasets, test cases, and benchmark environments that capture real‑world enterprise finance challenges.
• 4. Collaborate with AI researchers, machine learning engineers, and product teams to evaluate, validate, and improve finance‑focused models and agentic systems.
• 5. Analyze model behavior, failure modes, and performance trends to generate actionable insights and guide research priorities.
• 6. Publish internal research findings, technical reports, and best practices that contribute to the broader understanding of AI capabilities in finance.
• 7. Stay current with advances in AI, machine learning, financial modeling, evaluation science, and agent architectures, incorporating emerging techniques into research initiatives.
• 8. Help establish research standards and thought leadership for enterprise financial intelligence and AI evaluation.
• 9. Foster a culture of scientific rigor, experimentation, and collaborative innovation within a distributed research environment.

What We're Looking For

• 1. Advanced degree in Finance, Economics, Financial Engineering, Quantitative Finance, or a related field (PhD strongly preferred; MBA, CFA, or equivalent expertise also considered).
• 2. Deep domain expertise in one or more areas of finance, including investment research, capital markets, risk management, corporate finance, accounting, or financial analysis.
• 3. Demonstrated experience conducting rigorous research, developing analytical methodologies, or building evaluation frameworks in finance or related quantitative disciplines.
• 4. Strong ability to translate ambiguous real‑world financial problems into measurable research questions and evaluation criteria.
• 5. Exceptional analytical and critical‑thinking skills, with a track record of solving complex, multidisciplinary problems.
• 6. Excellent written and verbal communication skills, including experience producing research reports, technical documentation, or thought leadership content.
• 7. Experience working in highly collaborative, cross‑functional environments involving research, engineering, and product stakeholders.

Preferred Qualifications

• 1. Experience evaluating, benchmarking, or researching large language models, AI agents, reasoning systems, or enterprise AI applications.
• 2. Familiarity with agentic workflows, AI evaluation methodologies, synthetic data generation, or model alignment techniques.
• 3. Knowledge of contemporary research in machine learning, financial AI, decision intelligence, or computational finance.
• 4. Experience designing industry benchmarks, assessment frameworks, or performance standards.
• 5. Publication record in academic conferences, journals, industry research, or influential technical publications.
• 6. Proficiency with data analysis, experimentation, or quantitative research tools (e.g., Python, SQL, statistical analysis, or machine learning frameworks).

Compensation & Benefits Notice

The national pay range for this full‑time position is base salary of $200,000 –$250,000. All employees are eligible for equity compensation, and employees may also receive performance‑based bonuses, dependent on role and subject to company policies. micro1 provides a comprehensive benefits package, including up to 100% reimbursement for health‑insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits designed to support a high‑performing, remote‑first workforce.

micro1 is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to [e-mail].

Our hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision‑making.

Disclaimer

The information contained in this job posting, including but not limited to role responsibilities, qualifications, compensation, and benefits, is provided for informational purposes only and does not constitute a binding offer of employment. micro1 reserves the right to amend, modify, or withdraw any portion of this posting at its sole discretion and without prior notice. All employment decisions are made in accordance with applicable laws and regulations.

What You’ll Do

• 1. Design, own, and evolve evaluation frameworks for AI agents operating in financial domains, including benchmark suites, scoring methodologies, quality rubrics, and research‑grade evaluation protocols.
• 2. Conduct original research on financial reasoning, decision‑making, and workflow automation, translating findings into measurable improvements in AI system performance.
• 3. Develop and curate datasets, test cases, and benchmark environments that capture real‑world enterprise finance challenges.
• 4. Collaborate with AI researchers, machine learning engineers, and product teams to evaluate, validate, and improve finance‑focused models and agentic systems.
• 5. Analyze model behavior, failure modes, and performance trends to generate actionable insights and guide research priorities.
• 6. Publish internal research findings, technical reports, and best practices that contribute to the broader understanding of AI capabilities in finance.