Research Scientist
About the role
Research Scientist role at ATG, an AI lab building frontier reasoning systems for financial markets. Drive original research in AI/ML, develop new models and architectures, and translate theory into real-world deployments.
Responsibilities
- Formulate and explore open questions in deep learning, reinforcement learning, and agent-based AI.
- Develop novel architectures, algorithms, and theoretical insights.
- Collaborate with engineers to implement, experiment, and iterate rapidly.
- Publish, present, and contribute to the broader research community.
- Mentor and support the next generation of technical talent.
Qualifications
- Demonstrated track record of impactful AI/ML research (papers, open-source, or novel deployments).
- Deep expertise in at least one of: LLMs, RL, agent-based systems, generative modeling, theory of intelligence.
- Strong mathematical background (probability, optimization, statistics).
- Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX).
- Ability to turn theory into robust, practical code.
- Up-to-date on the latest research in LLMs from reading papers, articles, or re-implementing breakthroughs.
- Expertise in leveraging the latest AI tools (Cursor, Claude Code, Codex, etc) to increase productivity & code output while maintaining high code quality, maintainability, and structure.
Skills

About Autonomous Technologies Group
Superintelligent financial advisor
Autonomous is a superintelligent financial advisor at 0% advisory fees. Today, managing your money means one of two bad options: DIY your money: You end up with accounts everywhere (401k, IRAs, brokerage, crypto, savings, equity, secondaries). Your spreadsheet is always wrong. You make expensive mistakes because this isn't your full-time job. Hire a financial advisor: They'll manage your money and charge 1-2% of assets annually. Run that math over multiple decades and you're handing over half your net worth to fees. Neither path can economically deliver the sophisticated, personalized strategies the ultra-wealthy use to compound wealth: strategic tax-loss harvesting across individual securities, systematic risk management, portfolio-backed borrowing to defer capital gains, access to alternatives, etc. These aren't secret – they're just economically impossible to deliver at scale through traditional human advisors. Robos were supposed to fix this, but they were designed in a pre-AI world. In practice they just manage cookie-cutter portfolios. They don’t coordinate across your 401(k), taxable accounts, mortgage, equity, and cash flow, they don’t help with real decisions like job offers, windfalls, or concentrated stock, and they don’t deliver institutional strategies. That’s why, even after a decade plus, the biggest robos are still <$100B AUM while old-school advisors like Raymond James / Edward Jones sit on trillions. We’re doing for financial advising what Robinhood did for brokerages. Think of it as a full-stack, AI-native wealth strategist that brings billionaire-style playbooks to ordinary investors. Autonomous is built around a frontier-scale reasoning engine—an AI that perceives global events as they unfold, understanding their deeper implications for markets and and most importantly, how these events will impact your investments.
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