AI/ML – Investment Services

AI/ML – Investment Services A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Build and scale core backend services and platforms that power generative AI applications and data infrastructure used across the firm’s investment workflows Design and implement high-throughput, low-latency data pipelines to ingest, normalize, and serve both structured and unstructured data Develop robust APIs and microservices to support model inference, feature serving, and downstream applications Integrate generative AI tools and model-serving workflows into production, including embedding stores, retrieval components, and fine-tuning pipelines Optimize system performance, cost, and reliability through profiling, capacity planning, and architectural improvements Implement automated testing, continuous delivery pipelines, monitoring, and incident response practices to maintain production health Partner with data scientists, AI engineers, product owners, and operations to translate models and prototypes into scalable, production-grade solutions Mentor engineers, lead code reviews, and establish engineering best practices for maintainability, security, and observability Own end-to-end delivery, operational runbooks, and metrics-driven measurement of feature impact and system reliability WHAT'S REQUIRED Bachelor’s degree in computer science, software engineering, or a related technical field Minimum 5+ years of professional experience building backend systems and production services Demonstrated experience designing and operating large-scale data engineering pipelines for both batch and streaming workloads Demonstrated hands-on engagement with generative AI tools or development workflows, including model inference, embeddings, or model fine-tuning Proficiency in P ython and in at least one systems language such as Java, Go, or C++ Strong experience with cloud platforms and services for compute and storage and with containerization and orchestration technologies such as Kubernetes Proven experience with databases and messaging or stream-processing technologies for high-throughput workloads Experience designing and implementing APIs, microservices, CI/CD pipelines, automated testing, and observability tooling Excellent verbal and written communication skills and demonstrated...