AI/ML – Investment Services
Point72 Asset Management - Bengaluru, India
Posted Feb 4, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
-
- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Offered From the posting source checked Jun 20, 2026
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Offered From the posting source checked Jun 20, 2026
- Verification
- Not verified
- Salary
- Not verified
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Market context
- U.S. role benchmark (BLS OEWS)
- $116,543 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +9.8% - Much faster than average
Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Company
- Company stage
- Public-company From the posting source checked Jun 20, 2026
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
AI/ML – Investment Services Bengaluru, India 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
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