Startups · AI

Member of Technical Staff (Research Engineering)

Autonomous Technologies Group · New York City · On-site

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About Autonomous Technologies Group

Superintelligent financial advisor. Backed by Y Combinator.

About the role

You’ll bridge research and engineering—rapidly implementing, experimenting with, and scaling new algorithms and models. You’ll work closely with scientists and founders to translate ideas into high-performance systems, and will operate across the stack from prototyping to deployment. Prototype and scale experimental models (LLMs, RL agents, agentic systems) on large, real-world data.

What they're looking for

  • 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
More about this role

ATG (Autonomous Technologies Group) is an AI lab deploying frontier reasoning systems within financial markets.

Founders: Early GPU cloud (9 figure exit).

Investors: Garry Tan / YC + Founder of one of the most successful quant funds, BoxGroup (Plaid, Ramp, Stripe), top-tier angels.

You’ll bridge research and engineering—rapidly implementing, experimenting with, and scaling new algorithms and models. You’ll work closely with scientists and founders to translate ideas into high-performance systems, and will operate across the stack from prototyping to deployment.

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.

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...

Read the full posting on Autonomous Technologies Group's site ↗

Engineering

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