Responsibilities: • Support quantitative research and trading by designing, implementing and improving proprietary libraries and machine-learning pipelines• Leverage modern computer architectures to improve throughput or reduce cost• Identify compute waste and 10 bottlenecks and deliver cost-efficient solutions at scale• Measure delivered improvements using quantitative metrics• Customize solutions for results and adoption with partner teams Qualifications: • Experience working in C++ and/or Python• Experience with identifying performance bottlenecks: at a low-level, induced by the OS, from software architecture, or in a distributed system• Familiarity with high-performance computer architectures• Strong problem solving skill and quantitative orientation• Proven track record of being a goal-oriented individual• Ability to work independently and prioritize high-impact projects• Strong communication and interpersonal skills applicable to a dynamic research environment• Minimum Master’s degree (or equivalent experience) in Computer Science or related field