AI/ML – Investment Services
crypto:applicationdataIC4Senior Management
Compensation
Not disclosed
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 e