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Salary
≈ $33k – $71k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 7+ years exp
Visa
Sponsors visas in United States, Ireland; no register of this country names it

Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on Jul 21, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

As a Data Scientist Senior Associate in Asset and Wealth Management AI Engineering team, you will play a lead role as a seasoned member of our global AI team. Your responsibilities will entail hands-on development of high-impact business solutions through data analysis, developing cutting-edge ML and LLM models, and deploying these models to production environments on AWS or Azure.

You’ll combine your years of proven development expertise with a never-ending quest to create innovative technology through solid engineering practices. Your passion and experience in one or more technology domains will help solve complex business problems to serve our Private Bank clients. As a constant learner and early adopter, you’re already embracing leading-edge technologies and methodologies; your example encourages others to follow suit.

Job Responsibilities

  • Collaborate with firmwide AI/ML teams, Business and Product Partners, peers in geographically dispersed teams, and colleagues across JPMorgan AWM’s lines of business and functions to drive alignment, accelerate adoption of common AI capabilities, and deliver impactful solutions
  • Hands-on architecture and implementation of lighthouse ML and LLM-powered solutions
  • Design and implement highly scalable and reliable data processing pipelines and deploy model inference services
  • Experiment, develop, and productionize high-quality machine learning models, services, and platforms to make a huge technology and business impact
  • Deploy solutions into public cloud infrastructure

Required Qualifications, Capabilities, and Skills

  • MS in Computer Science, Statistics, Mathematics, or Machine Learning
  • Minimum 7 years of development experience, with at least 4 years working on AI solutions.
  • Experience in using LLMs (OpenAI, Anthropic, or other models) to solve business problems, including full workflow toolset such as tracing, evaluations, and guardrails;
  • Must have strong programming skills in Python
  • Deep knowledge in Data Structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, and Statistics
  • Demonstrated ability to perform independent end-to-end solution design, with attention on modern architecture, scalability and security
  • Expert knowledge of one of the cloud computing platforms , Amazon Web Services (AWS), Azure, Kubernetes
  • Knowledge of data management, including data model design, as well as real-time data processing on both SQL (such as Postgres) and NoSQL stores (such as OpenSearch and Redis)
  • Proven leadership capacity, including new AI/ML idea generation and GenAI-based solutions
  • Excellent communication skills and ability to communicate with senior technical and business partners

Preferred Qualifications, Capabilities, and Skills

  • Experience working in the financial domain with a large financial institution in Asset and Wealth Management, Brokerage, or Investment Banking will be an added advantage
  • Understanding of LLM fine-tuning and small language model inference is a plus
  • Ability to develop full-stack products, utilizing modern JavaScript and TypeScript frameworks, such as Next.js and Svelte
  • Knowledge of other high-performance languages, such as Go or Rust
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