Reads like an AI Engineer role: building products on existing AI models.
London, United Kingdom
Live, first seen by us 36 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Design scalable architecture for LLM-powered investment tools with governance and access control
Build retrieval-augmented generation capabilities, including chunking, embeddings, and reranking
Create reliable data and knowledge pipelines that turn enterprise content into AI inputs
Implement evaluation and observability for AI systems covering quality, latency, and cost
Partner with portfolio managers and research teams to turn investment processes into solutions
Design and implement scalable architecture for LLM-powered investment tools, ensuring integration, governance, observability, and access control
Develop context-management and retrieval-augmented generation (RAG) capabilities, including ingestion, chunking, metadata, embeddings, hybrid search, reranking, and grounded outputs
Create reliable data and knowledge pipelines that transform enterprise content into high-quality inputs for AI applications
Implement evaluation and end-to-end observability for AI systems, optimizing for quality, groundedness, task completion, latency, token usage, cost, reliability, and business impact
Partner with portfolio managers and research teams to understand investment processes and translate them into practical solutions
Required Qualifications, Capabilities, and Skills: - Hold a Master’s degree or PhD in computer science, statistics, mathematics, engineering, econometrics, or a quantitative field - Demonstrate a strong foundation in statistics, probability, experimental design, and machine learning, with sound judgment in method selection and interpretation
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Day 36
Similar jobs usually come down between day 4 and day 77.
Well past JPMorgan Chase’s usual: its jobs come down by about day 15.
From 51 similar postings that came down, and 1,000 of JPMorgan Chase’s. Coming down is not always a hire.
358 open jobs
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- Apply practical knowledge of prompt and context design, embeddings, vector and keyword search, reranking, model selection, and optimization for quality, latency, and cost - Exhibit strong Python and SQL skills, with experience using common data and machine learning libraries and frameworks - Show numerical intuition and understanding of financial markets, investment research, portfolio construction, risk, performance, and investment data
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We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Are you ready to make an impact at the intersection of finance and technology? At JPMorgan Chase, you’ll help drive innovation in investment decision-making and client engagement. You’ll work with advanced analytics, enterprise data platforms, and generative AI solutions that power our global business. We offer career growth, mobility, and the opportunity to collaborate with talented professionals across the firm. Your skills will help us deliver secure, scalable, and measurable solutions for our clients.
As an Applied AI & Machine Learning Senior Associate in the Asset Management Data Science Team, you will build the technical foundation for intelligent investor tools. You will design context-management capabilities, develop LLM-powered applications, and create reliable pipelines for enterprise and investment data. You will partner with investment, data science, engineering, product, and control teams to turn complex financial workflows into secure, scalable solutions. You will join a small, globally connected team with the resources and impact of one of the world’s largest financial institutions.
Job Responsibilities:
Required Qualifications, Capabilities, and Skills:
Preferred Qualifications, Capabilities, and Skills:
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London, United Kingdom
- Build and scale AI applications and automated workflows using models, retrieval, and tools, with orchestration for state management and human oversight - Develop context-management and retrieval-augmented generation (RAG) capabilities, including ingestion, chunking, metadata, embeddings, hybrid search, reranking, and grounded outputs - Create reliable data and knowledge pipelines that transform enterprise content into high-quality inputs for AI applications
No clear work-authorization passage found. Eligibility is unconfirmed.