Quantitative Development - DevOps Engineer

Quantitative Development - DevOps Engineer About Millennium Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors. Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact. Meet the Team The Central Liquidity Strategies business within Execution Services manages a range 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. The team operates at the intersection of research, engineering, and production infrastructure, supporting the platforms, tooling, and operational foundations required to scale research workflows and deploy critical applications reliably.

Design and implement infrastructure that improves research and development velocity across the CLS environment Advise on, establish, and enforce engineering and infrastructure best practices to support scalable, reliable research and production workflows Evaluate state-of-the-art tools and practices and apply sound judgment in selecting the right solutions for CLS research and development use cases Build dependable, reproducible polyglot environments across Python, native extensions, and CUDA that support fast research iteration and smooth production deployment Strengthen packaging standards and development practices for large research codebases Partner with cloud-based infrastructure to help scale research workloads and improve execution efficiency Develop CI/CD pipelines, monitoring solutions, and job automation frameworks for research processes and live trading applications Create solutions that help researchers and developers profile, monitor, and better understand application and infrastructure performance What You Bring   7+ years of experience in research-focused DevOps environments such as HPC, machine learning research, or quantitative research, along with experience supporting high-availability production deployments Strong communication skills and the ability to work effectively with a wide range of stakeholders in a team environment Demonstrated leadership skills, including the ability to work within constraints, make decisions under time pressure, and take ownership of outcomes Strong development skills, including experience writing clean, robust, and testable code to automate infrastructure management and deployment processes Solid systems knowledge, including familiarity with Linux internals, software deployment, and package management Strong understanding of Python internals and modern Python packaging standards Familiarity with current packaging and build tooling, including uv and hatchling Experience with tools and platforms such as Nix, Conda, Pixi, Kubernetes, and containers