Applied AI ML - Associate/VP

🏢 JP Morgan
📍 LONDON, United KingdomFull-timeOn-site
📅 Posted: 1w ago🔄 Updated: 1w ago
CV%
✨ AI Summary
We are seeking an Applied AI Scientist with strong machine learning experience to join our AI Technologies team at J.P. Morgan. This hands-on role involves building practical machine learning and generative AI solutions that can be moved from experimentation into production. You will collaborate closely with product owners, data engineers, software engineers, and other ML practitioners to design, test, improve, and deploy AI/ML capabilities at scale. Key responsibilities include applying machine learning, deep learning, and generative AI techniques to business problems, designing and evaluating ML experiments, working with large language models and AI agents, writing production-quality code from proof of concept to deployment, and improving model accuracy, reliability, and performance. The ideal candidate will have a STEM degree or equivalent practical experience, applied experience with ML and deep learning methods, and proficiency in Python and other programming languages like Java or C/C++. Experience with large language models, deploying ML models on cloud platforms, and familiarity with AWS tools are preferred.
Required Skills
Information Technology
PythonJavaCMachine LearningDeep LearningGenerative AI
Other
ownership
Soft Skills & Professional Competencies
Attention to DetailCollaborationCommunication
Nice to have:
Information Technology
Large Language ModelsAI AgentsModel DeploymentCloud Computing
Finance, Legal & Governance
Sage
Other
AWS EKS
Requirements
STEM degree or equivalent practical experience is required. Candidates must have applied experience with machine learning, deep learning, and generative AI methods, along with proficiency in Python and programming experience in Java, C/C++, or similar languages. The role demands the ability to take ownership, deliver results with limited supervision, and possess strong attention to detail and effective communication skills for team collaboration.
Description

We’re looking for an Applied AI Scientist with strong machine learning experience to join our AI Technologies team.

In this role, you’ll help build practical machine learning and generative AI solutions that can move from experimentation into production. You’ll work closely with product owners, data engineers, software engineers, and other ML practitioners to design, test, improve, and deploy AI/ML capabilities at scale.

This is a hands-on role for someone who enjoys solving technical problems, writing code, experimenting with new approaches, and turning ideas into reliable systems.

Job Responsibilities:

  • Apply machine learning, deep learning, and generative AI techniques to business problems
  • Design, run, and evaluate ML experiments using current tools and frameworks
  • Work with large language models, AI agents, and related methods to enhance ML workflows
  • Write production-quality code and own solutions from proof of concept to deployment
  • Improve model accuracy, reliability, and performance by identifying optimization opportunities
  • Partner with product and engineering teams to build scalable and maintainable solutions
  • Contribute technical expertise to model design and platform implementation decisions
  • Share knowledge and help elevate the technical standard of our ML work

 

Required Qualifications, Capabilities, and Skills:

  • STEM degree or equivalent practical experience
  • Applied experience with machine learning and deep learning methods
  • Proficiency in Python and programming experience in Java, C/C++, or similar languages
  • Ability to take ownership of tasks and deliver results with limited supervision
  • Strong attention to detail and follow-through
  • Effective communication skills and ability to collaborate in a team environment
  • Experience working with engineers, product managers, and ML practitioners

 

Preferred Qualifications, Capabilities, and Skills:

  • Experience with large language models, including agents, planning, or reasoning techniques
  • Experience building and deploying ML models on cloud platforms
  • Familiarity with AWS tools such as SageMaker, EKS, or similar services
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🎯 Overalli74%
⚡ Skillsi85%
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Ontology Match: 85.0
Matched:✓ Requirements Matching✓ Ontology Skills Mapping
📜 Eligibilityi49%
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Local: 19600%
🏗️ Career Fiti91%
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Seniority: 91.0
📋 Requirementsi67%
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Domain: 67.0
🔥 Motivationi78%
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Title Fit: 78.00