Quantitative Developer, Research & ML Engineering, Systematic Macro

Millennium Management LLC
London, UK
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Big Data C++ (Programming Language) Distributed Systems Integrated Development Environments Python (Programming Language) Machine Learning Software Engineering Deep Learning Parallel Computation Linux Development Information Technology

Requirements

parameter search, and a streamlined path from research to production.LocationLondonPrincipal ResponsibilitiesDesign, train and productionize large-scale machine learning models across both classical and deep learning approaches, applied to high-frequency dataEnhance and optimize the pod’s end-to-end machine learning pipeline, from large-scale data processing and distributed computation to scalable parameter search and validationContribute to improving the speed, scalability, and reliability of the pod’s wider signal development environment, ensuring consistent and efficient migration from research to productionPartner with broader technology teams to make effective use of shared internal platforms and ServicesQualificationsMaster’s or PhD/Post doctorate in Computer Science, Mathematics, Statistics, Engineering, Physics, or a related quantitative discipline, from a leading institutionPreferred Technical Skills3+ years of professional experience in software engineering, quantitative development, or a related computational roleExperience developing and validating machine learning models on large, complex datasets, across both classical and deep learning approaches, in industry or academiaExperience building distributed computing systems for machine learning applicationsStrong Python programming skills beyond the standard research stack - parallelism, distributed compute, and native acceleration such as Python or C++ bindingsFamiliarity with C++ is a strong plus, alongside the software engineering fundamentals to pick it up quicklyExperience building data-intensive tools, research workflows, or model development infrastructureStrong Linux development experienceExperience building agentic AI systems - tool use, orchestration, and evaluationHigh Valued ExperienceExperience with backtesting and awareness of common research pitfalls such as overfitting, lookahead bias, and survivorship biasUnderstanding of systematic trading strategies and quantitative research workflowsKnowledge of market microstructureExperience supporting production research workflows or model deployment in a front-office environmentRecruiter:Brian KimmelHiring Manager:John DowneyDepartment:Trading

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