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JPMorganChase

Applied AIML Lead-Python & Agentic AI

Posted Yesterday
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Hybrid
Glasgow, Lanarkshire, Scotland
Expert/Leader
Hybrid
Glasgow, Lanarkshire, Scotland
Expert/Leader
Leads the design, development, and deployment of production AI, ML, LLM, and generative AI solutions. Manages and mentors ML and MLOps engineers, builds scalable model deployment pipelines, fine-tunes generative models for NLP, evaluates model performance, implements monitoring, and communicates results to technical and non-technical stakeholders. The role also applies advanced prompting, RAG, and emerging AI techniques to enterprise use cases.
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The Applied Artificial Intelligence and Machine Learning (Applied AI/ML) team within Infrastructure Platforms is transforming how the firm delivers strategic infrastructure platforms-based solutions—both by applying AI/ML within engineering workflows and by building scalable AI hosting platforms and capabilities for enterprise use. 

As a Machine Learning Lead Software Engineer at JPMorgan Chase within the Governance & Controls Technology AI/ML team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.  

Job responsibilities 

  • Work closely with product managers, data scientists, ML engineers, and other stakeholders to understand requirements and prioritize use cases. 
  • Design, develop, and deploy state-of-the-art AI/ML/LLM/GenAI solutions to meet business objectives. 
  • Manage, mentor, and guide a team of ML and MLOps engineers. 
  • Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency. 
  • Implement optimization strategies to fine-tune generative models for specific NLP use cases, ensuring high-quality outputs in summarization and text generation. 
  • Conduct thorough evaluations of generative models (e.g., GPT-5.5), iterate on model architectures, and implement improvements to enhance overall performance in NLP applications. 
  • Implement monitoring mechanisms to track model performance in real-time and ensure model reliability. 
  • Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences. 
  • Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality. 

Required qualifications, capabilities, and skills 

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field 
  • demonstrated experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production. 
  • Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API. 
  • Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API. 
  • Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization. 
  • Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly GANs, VAEs. 
  • Ability to identify and address AI/ML/LLM/GenAI challenges, implement optimizations and fine-tune models for optimal performance in NLP applications. 
  • Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects. 
  • A portfolio showcasing successful applications of generative models in NLP projects, including examples of utilizing OpenAI APIs for prompt engineering. 

    Preferred qualifications, capabilities, and skills 

  • Familiarity with the financial services industries. 
  • Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG). 
  • Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies. 

  

About UsJ.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
  
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
About the TeamOur professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

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