Applied AIML Lead-Python & Agentic AI

JPMorgan Chase & Co.; Glasgow; On-site; GBP 90,000 - 130,000; Full time

Job summary

JPMorgan Chase & Co. in Glasgow seeks a Lead Software Engineer specializing in Applied AI/ML to design and deliver trusted AI products within Governance & Controls Technology AI/ML. You will craft secure, scalable ML solutions and guide a team across multiple domains.

You will deploy models, optimize NLP tasks, monitor performance in real-time, and communicate results to technical and non-technical stakeholders. This role emphasizes collaboration and staying ahead in AI research.

Qualifications

• Experience deploying production ML models in scalable systems.
• Proficiency in Python and OpenAI API for model development.
• Familiarity with ML frameworks and cloud platforms.
• Strong collaboration across cross-functional teams and stakeholders.
• Portfolio of generative NLP projects using OpenAI APIs.

Responsibilities

• Collaborate with product managers, data scientists, ML engineers and stakeholders to prioritize use cases.
• Design, develop, and deploy state-of-the-art AI/ML/GenAI solutions aligning with business goals.
• Mentor and guide a team of ML and MLOps engineers.
• Build and maintain automated pipelines for model deployment ensuring scalability and reliability.
• Fine-tune generative models for NLP use cases to deliver high-quality outputs.

Skills

Python

Applied AI/ML

NLP / GenAI

MLOps / CI/CD

Communication

Education

Bachelor's or Master's in CS/Engineering

Tools

OpenAI API

TensorFlow

PyTorch

Docker

Kubernetes

Cloud (AWS/Azure/GCP)

Job description

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.