Quantitative Development - DevOps Engineer

Quantitative Development - DevOps Engineer Job Function Summary The Central Liquidity Strategies (CLS) business manages a number of portfolios and products designed to optimize the firm’s trading and execution approach by providing internal liquidity solutions for portfolio managers on both a risk and agency basis. We are seeking a highly driven, results-oriented, and opinionated dev ops leader with experience in handling research infrastructure, deploying critical applications, and operating on large amounts of data to create battle-tested infrastructure and improve the research development experience. Principal Responsibilities Leadership: the candidate will design and implement infrastructure, and advise on and enforce best practices to maximize research and development velocity Research: the candidate is expected to keep up with the state-of-the-art tools that are being used in the field and continuously evaluate what the best tools and practices are for our use cases Machine Learning Operations (MLOps) + Development Experience (DevEx): create dependable and reproducible polyglot (Python, native extensions, CUDA) environments for rapidly iterating research projects that can be easily deployed to prod Enforce best practices and packaging standards for large research codebases Work with the cloud to help scale research jobs Infrastructure automation: develop CI/CD pipelines for research processes and live trading apps develop robust monitoring solutions for infrastructure and deployed applications automate recurring jobs with tools like Airflow/Prefect Performance engineering: Be familiar with best practices for profiling, monitoring performance to assist with performance investigations Develop solutions that empower researchers and developers to understand the performance of their code Qualifications/Skills Required Experience: 10+ years of experience with research focused DevOps (HPC, ML research, quant research) and experience with high-availability production deployments Strong communications skills and ability to work with many stakeholders in a team environment Leadership skills: ability to work with constraints, make decisions under time pressure, and own your work Development skills: Experience writing clean, robust, and testable code for automating processes pertaining to infrastructure management and deployment Systems knowledge: familiarity with Linux internals understanding of package management, how software is deployed on systems Python: Strong understanding of Python internals Familiarity with the latest standards in the packaging ecosystem (uv), build tools like hatchling Familiarity with tools like: Nix, Conda, Pixi, and containers