Principal Machine Learning Engineer

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About this role

Principal Machine Learning Engineer Chicago, United States; Hong Kong, Hong Kong; New York, United States; Sydney, Australia At IMC, we believe technology is the foundation of our competitive edge - and machine learning is increasingly central to how we trade. Over the past few years, we've been steadily building our machine learning capabilities: developing infrastructure, growing our in-house GPU cluster, deploying models into production, and partnering closely with quant researchers and traders to generate real impact. Now we're expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows. We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform - influencing architecture, driving best practices, and solving high-leverage problems. You'll work alongside researchers and technologists to design the systems that power experimentation, training, and deployment of ML models - and help set the direction for how machine learning is done at IMC as we scale. If you've built ML infrastructure at scale elsewhere and are looking for a role where your ideas will genuinely help shape our firm's future - we'd love to hear from you. Your Core Responsibilities: - Design and build end-to-end infrastructure for training, evaluation, and productionization of ML models, working closely with our HPC engineers who manage our on-prem compute cluster - Influence foundational choices around data access, compute orchestration, experiment tracking, model versioning, and deployment pipelines - Partner with quant researchers to accelerate iteration cycles, tighten feedback loops, and bring

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