London, United Kingdom
Actively hiring, first seen by us 2 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
Currently enrolled in a PhD or MS program in Computer Science, Electrical Engineering, Mathematics, Operations Research, Data Science, or a related quantitative field, with an expected graduation date between December 2027 and August 2028
Build prototypes of multi-step agentic AI systems that use tools
Apply LLM techniques such as retrieval-augmented generation and fine-tuning
Develop evaluation frameworks for quality, reliability, and safety of LLM outputs
Run exploratory data analysis, feature engineering, and model development
Document methodology and present findings to technical and business audiences
Design and build prototypes of agentic AI systems, including multi-step workflows that use tools and reason across tasks
Apply and experiment with LLM techniques such as retrieval-augmented generation, tool and function calling, fine-tuning, and agent harness design
Develop evaluation frameworks to measure the quality, reliability, and safety of LLM and agent outputs
Perform exploratory data analysis, feature engineering, model development, and evaluation using structured and unstructured datasets
Document methodology, assumptions, and results so work can be reproduced, and present findings and key learnings to technical and business audiences
Required qualifications, capabilities, and skills - Currently enrolled in a PhD or MS program in Computer Science, Electrical Engineering, Mathematics, Operations Research, Data Science, or a related quantitative field, with an expected graduation date between December 2027 and August 2028 - Solid background in at least one of: large language models and agentic AI, natural language processing, speech recognition, or personalization/recommendation, with familiarity with current state-of-the-art methods
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
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Day 2
Early. Similar jobs usually come down between day 7 and day 71.
At JPMorgan Chase, jobs usually come down by about day 15.
From 4,682 similar postings that came down, and 930 of JPMorgan Chase’s. Coming down is not always a hire.
395 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Hands-on exposure to modern LLM application patterns such as prompting, embeddings, retrieval-augmented generation, tool/function calling, structured outputs, and multi-step or agentic workflows - Strong Python skills, including deep learning frameworks (PyTorch or TensorFlow), the Hugging Face ecosystem, and core data libraries (NumPy, Pandas, scikit-learn) - Clear written and spoken communication for both technical and business audiences, and the ability to work both independently and on a team
Complete your application on jpmc.fa.oraclecloud.com. The employer’s form will show what is required.
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
At JPMorgan Chase, AI is transforming how we operate on a global scale. We invest over $18 billion annually in technology, including innovation, data, and security, to shape the future for our clients, communities, and employees. Housed within The Chief Data & Analytics Office (CDAO), the Machine Learning Center of Excellence (MLCOE) creates and deploys AI and machine learning solutions for complex business challenges across flagship AI deployments at the firm. Our solutions power financial products, boost productivity, and strengthen risk management across the firm.
As a Summer Associate within MLCOE, you will apply advanced LLM and agentic AI methods to complex problems in areas such as natural language processing, question answering, speech recognition and understanding, reinforcement learning, post-training and recommendation systems. Working alongside MLCOE mentors, business experts, and technologists, you will own a research project from start to finish. This role offers hands-on experience solving real business problems at scale while learning from experienced AI researchers and engineers. Learn more about MLCOE at jpmorgan.com/mlcoe.
Our Summer Associate Internship Program begins in June, depending on your academic calendar. Your professional growth and development will be supported throughout the internship program via project work related to your academic and professional interests, mentorship, an engaging speaker series with our senior leaders and more. Your project will have a direct impact on JPMorgan’s businesses, will be integrated into our product pipelines, or be part of published research in top AI conferences. Full-time employment offers may be extended upon successful completion of the program within our hybrid work model.
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Required qualifications, capabilities, and skills
Preferred qualifications, capabilities, and skills
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London, United Kingdom
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