New York | $200,000–$300,000 Base + Bonus
I'm working with one of the world's leading quantitative trading firms on a really interesting Machine Learning Research Engineer position.
This is a hands-on role sitting between ML research, software engineering and infrastructure. You'll be the person stress-testing the ML platform, running new models at scale, finding bottlenecks and helping shape what gets built next.
You'll be working with Python, PyTorch, distributed compute, GPUs, Ray and AI/agentic workflows, building tools that allow researchers to move from idea to experiment much faster.
I'm looking for someone with strong software engineering fundamentals who has hands-on experience with machine learning at scale and distributed systems.
Experience with quant trading, time-series data or large-scale research environments would be a big plus, but isn't essential.
$200k–$300k base + bonus.
If you're a strong ML engineer who likes getting into the weeds and building things that other researchers actually use, I'd love to hear from you.
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