About the Position
We are seeking highly motivated and curious individuals from academia and industry to join our expanding team and advance our machine learning research.
On our Machine Learning team, you will develop deep learning models that support complex trading strategies, leveraging a rapidly growing computing cluster with thousands of high-performance GPUs. Trading presents unique challenges—large-scale models, non-stationary datasets, and competitive multi-agent environments—that require innovative solutions.
Researchers, engineers, and traders work closely together to train models, design systems, and deploy strategies. Your day-to-day work could involve analyzing market data, tuning hyperparameters, optimizing distributed training, or studying how models behave in production.
Your deep knowledge of the machine learning landscape—spanning LLMs, image models, reinforcement learning agents, recommendation systems, and classical ML methods—will shape the future of our ML initiatives. You will train models for the next generation of deep learning-based strategies, develop fundamental insights into new markets, and contribute to team growth through mentorship, conference participation, and knowledge sharing.
About You
We are looking for candidates with a PhD in Computer Science, Machine Learning, Statistics, or a related field, who are passionate about solving challenging problems. The ideal candidate brings:
Practical experience working on empirical ML problems
Strong logical and mathematical problem-solving abilities
Intellectual curiosity and engagement with state-of-the-art research across multiple ML domains
Fluency with a diverse set of models, architectures, and techniques
Hands-on coding skills to rapidly implement and iterate on ideas, preferably in Python and familiar ML frameworks
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