Member of Technical Staff (Research Engineering)
About the role
ATG is an AI lab deploying frontier reasoning systems within financial markets. The role bridges research and engineering to rapidly implement, experiment with, and scale new algorithms and models, translating ideas into high-performance systems across the stack from prototyping to deployment.
Responsibilities
- Prototype and scale experimental models (LLMs, RL agents, agentic systems) on large, real-world data.
- Build tools and pipelines for training, evaluation, and analysis.
- Implement state-of-the-art research from papers and iterate in collaboration with scientists.
- Own the full ML lifecycle: data engineering, experimentation, training, and deployment.
- Operate in a highly autonomous, engineering-driven environment.
Qualifications
- Strong background in deep learning, reinforcement learning, or computational modeling.
- Expert-level Python and significant experience in ML frameworks (PyTorch, JAX, TensorFlow).
- Ability to translate research into robust, scalable systems.
- Experience with distributed computing or large-scale ML pipelines.
- Demonstrated curiosity and hands-on experimentation skills.
- 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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