Member of Technical Staff (Research Engineering)
Automate your job search with Sonara.
Submit 10x as many applications with less effort than one manual application.1
Reclaim your time by letting our AI handle the grunt work of job searching.
We continuously scan millions of openings to find your top matches.
Job Description
About us
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.
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.
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.
Requirements
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.
Why Join ATG
We're building a small, elite team. If you're excited by AI, finance, and building from first principles, we’d love to meet you.
Work on AI with real stakes
Early team of repeat founders and ex-researchers from top companies
High agency, zero bureaucracy environment
Automate your job search with Sonara.
Submit 10x as many applications with less effort than one manual application.