Machine Learning Engineer – Elite Systematic Trading Team (NYC) 🚀

A world-class, technology-driven trading team in New York City is looking for a Machine Learning Engineer to help build the next generation of AI-powered research and production systems. This is a rare opportunity to work at the intersection of cutting-edge deep learning and high-performance trading, collaborating directly with top researchers, PMs, and technologists.

If you’re passionate about pushing the limits of AI in real-world, high-stakes environments — this team wants to hear from you.

💼 What You’ll Do

Build AI-driven agents to support production, monitor trading systems, and automate operational workflows.
Collaborate with AI researchers on projects like synthetic data generation, representation learning, and intelligent research workflow agents.
Research, design, and implement advanced deep learning models for sequential modeling, time-series forecasting, and representation learning.
Translate complex mathematical ideas into performant, production-ready code.
Work in a high-impact, data-driven environment with immense ownership and visibility.

🔍 We’re Looking For

PhD or PhD-track candidate in ML, Computer Science, or a related AI field.
Deep experience in sequential modeling, time-series forecasting, and neural networks.
Proficiency in Python (and ideally R) with strong experience in PyTorch or TensorFlow.
Background in research environments, algorithmic modeling, or applied ML.
Experience with LLMs, agent frameworks, context engineering, or NLP is a strong plus.
Strong analytical skills, independent research ability, and high attention to detail.
Clear communication and a commitment to excellence.

🌎 Location

📍 New York City – Onsite / Hybrid depending on candidate

🔥 Why This Role is Exceptional

You will be joining an elite technology team inside a highly successful systematic trading organization — working directly with leaders who are shaping the future of AI-driven trading. The impact is immediate, the projects are cutting-edge, and the growth potential is massive.

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