Senior Lead Software Engineer - Python

JPMorgan Chase & Co.; London; On-site; GBP 70,000 - 120,000; Full time

Job summary

JPMorgan Chase & Co. seeks a Lead Software Engineer to join the AI and Machine Learning Data Platform Team. The role involves optimizing ML workflows, utilizing advanced technologies, and developing solutions that enhance development processes. Candidates should have a strong background in machine learning, natural language processing, and programming, particularly in Python, to drive innovation in intelligent testing.

Qualifications

• Formal training in Computer Science or ML with applied experience.
• Intermediate proficiency in Python and experience with Java or C/C++.
• Experience in data science and ML for solving business challenges.

Responsibilities

• Serve as a subject matter expert on ML techniques and optimizations.
• Enhance ML workflows and conduct experiments with latest ML technologies.
• Collaborate with engineering teams for code development in Python.

Skills

Machine Learning

Natural Language Processing

Deep Learning

Attention to Detail

Team-Oriented Mindset

Education

MS or PhD in Computer Science or Machine Learning

Tools

PyTorch

TensorFlow

AWS

Job description

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Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the AI and Machine Learning Data Platform Team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will be responsible for conducting critical technology solutions across multiple technical areas within various business functions to support the firm's objectives.

The test engineering team is at the forefront of innovation, developing intelligent agents powered by top foundational models to enhance development and testing experiences. We build solutions that automate quality workflows, accelerate debugging, and enable smarter decision-making across SDLC. Join us in shaping the future of intelligent testing through cutting-edge AI and model-driven engineering.

Job Responsibilities

• Serve as a subject matter expert on a wide range of ML techniques and optimizations.
• Provide in-depth knowledge of ML algorithms, frameworks, and techniques.
• Enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
• Conduct experiments using the latest ML technologies, analyze results, and tune models.
• Collaborate with engineering teams to bring experimental results into production solutions, owning end-to-end code development in Python for both proof of concept/experimentation and production-ready solutions.
• Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks, working with product and engineering teams to deliver tailored solutions.
• Integrate Generative AI within the ML Platform using state-of-the-art techniques.

Required Qualifications, Capabilities, and Skills

• Formal training or certification (MS or PhD) in Computer Science, Machine Learning, or a related field, with applied machine learning experience.
• Experience in programming languages like Python (intermediate proficiency required), Java, C/C++, etc.
• Experience applying data science and ML techniques to solve business problems.
• Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs).
• Hands-on experience with machine learning and deep learning methods.
• Deep understanding of deep learning frameworks such as PyTorch or TensorFlow.
• Experience in advanced applied ML areas such as GPU optimization, fine-tuning, embedding models, inferencing, prompt engineering, evaluation, and RAG (Similarity Search).
• Ability to work independently on tasks and projects through to completion.
• Attention to detail, excellent communication skills, and a team-oriented mindset.

Preferred Qualifications, Capabilities, and Skills

• Master's degree in Computer Science, ML, or related areas.
• Experience with Ray, MLFlow, and/or other distributed training frameworks.
• Understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies.
• Deep knowledge of LLM techniques, including Agents, Planning, and Reasoning.
• Experience deploying ML models on cloud platforms such as AWS, Sagemaker, EKS, etc.
• Experience working with large-scale MLOps pipelines and deploying models to production.

About Us

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, and investors. We are committed to diversity and inclusion, valuing the talents of our diverse workforce. We do not discriminate on any protected attributes and make reasonable accommodations for all applicants and employees.

About the Team

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services, and payments, serving clients in over 100 countries with strategic advice, capital raising, risk management, and liquidity solutions.