Applied AI ML - Senior Associate - Machine Learning Engineer

JPMorganChase; Greater London; On-site; GBP 70,000 - 90,000; Full time

Job summary

JPMorganChase is looking for an Applied AI / ML Senior Associate Machine Learning Engineer to drive innovation in the Commercial & Investment Bank. This role requires a Master's or PhD in a quantitative discipline and strong experience with AI techniques, including Natural Language Processing and machine learning. Candidates should be proficient in PyTorch and familiar with cloud services. The position involves collaborating across teams to build scalable solutions and communicate findings effectively.

Qualifications

• Master's or PhD in a quantitative discipline (Computer Science, Mathematics, Statistics).
• Solid understanding of statistics, optimization, and machine learning theory.
• Extensive experience with PyTorch and data-science Python libraries.
• Experience containerizing applications for deployment (Docker).
• Ability to communicate technical information effectively.

Responsibilities

• Build robust Data Science capabilities across multiple business use cases.
• Collaborate with the software engineering team for Machine Learning integration.
• Research and analyze datasets using statistical and machine learning techniques.
• Communicate AI capabilities to technical and non-technical audiences.
• Document techniques and processes for industry compliance.

Skills

Statistics

Machine Learning theory

Natural Language Processing

PyTorch

Docker

Cloud computing (Azure, AWS, GCP)

Education

Master's or PhD in a quantitative discipline

Tools

pandas

Kubernetes

Job description

Job Description

Join a high performing team of applied AI experts to drive innovation and new capabilities in the Commercial & Investment Bank.

As an Applied AI / ML Senior Associate Machine Learning Engineer in the Applied AI ML team at JPMorgan Commercial & Investment Bank, you will combine cutting‑edge AI techniques with the company’s unique data assets to optimize business decisions and automate processes. You will advance the state‑of‑the‑art in AI as applied to financial services, leveraging research from Natural Language Processing, Computer Vision, and statistical machine learning. The role blends scientific research and software engineering, requiring deep understanding of both mindsets.

Job Responsibilities

• Build robust Data Science capabilities that can be scaled across multiple business use cases.
• Collaborate with the software engineering team to design and deploy Machine Learning services that integrate with strategic systems.
• Research and analyze datasets using a variety of statistical and machine learning techniques.
• Communicate AI capabilities and results to both technical and non‑technical audiences.
• Document approaches taken, techniques used, and processes followed to comply with industry regulation.
• Collaborate closely with cloud and SRE teams while leading the design and delivery of production architectures for our solutions.
• Act as an individual contributor, with optional management responsibility dependent on experience.

Required Qualifications, Capabilities, and Skills

• Master's or PhD in a quantitative discipline (Computer Science, Mathematics, Statistics).
• Solid understanding of fundamentals of statistics, optimization, and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders, etc.).
• Specialism or well‑researched interest in NLP.
• Broad knowledge of MLOps tooling for versioning, reproducibility, observability, etc.
• Experience monitoring, maintaining, and enhancing existing models over an extended period.
• Extensive experience with PyTorch and related data‑science Python libraries (e.g., pandas).
• Experience containerizing applications or models for deployment (Docker).
• Experience with a major public cloud provider (Azure, AWS, GCP).
• Ability to communicate technical information and ideas at all levels, conveying information clearly and building trust with stakeholders.

Preferred Qualifications, Capabilities, and Skills

• Experience designing/implementing pipelines using DAGs (Kubeflow, DVC, Ray).
• Experience with big data technologies.
• Have constructed batch and streaming microservices exposed as REST/gRPC endpoints.
• Experience with container orchestration tools (Kubernetes, Helm).
• Knowledge of open‑source datasets and benchmarks in NLP.
• Hands‑on experience implementing distributed/multi‑threaded/scalable applications.
• Track record of developing and deploying business‑critical machine learning models.

Equal Opportunity Employer

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.