Applied AI ML - Senior Associate - Machine Learning Engineer

Next Frontier Capital; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

JPMorgan Commercial & Investment Bank is seeking an outstanding Applied AI/ML Senior Associate Machine Learning Engineer to advance state‑of‑the‑art AI in financial services. You will blend research with software engineering, build reusable AI components, and help automate decisions across business domains.

The role emphasizes collaboration with cloud, SRE, and software teams, delivering production ML services while maintaining rigorous documentation and compliance practices.

Qualifications

• Masters or PhD in a quantitative field such as CS, math or stats.
• Strong foundation in statistics, optimization and ML theory.
• Specialism or strong interest in NLP.
• Broad knowledge of MLOps tooling for versioning and observability.
• Experience maintaining models over time.
• Proficient with PyTorch and Python data libraries.

Responsibilities

• Build scalable data science capabilities across multiple business use cases.
• Collaborate with software engineers to deploy ML services integrated with systems.
• Research data sets using statistical and ML techniques.
• Communicate AI capabilities and results to diverse audiences.
• Document approaches and processes to meet regulations.
• Collaborate with cloud and SRE teams to design production architectures.
• Act as individual contributor with potential for management depending on experience.

Skills

NLP expertise

ML theory

Data analysis

Statistical modelling

Cross-functional comms

Education

Masters/PhD in quantitative discipline

Tools

Docker

PyTorch

Pandas

Cloud platforms

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 be at the forefront of combining cutting‑edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance the state‑of‑the‑art in AI as applied to financial services, leveraging the latest research from fields of Natural Language Processing, Computer Vision, and statistical machine learning. You will be instrumental in building products that automate processes, help experts prioritize their time, and make better decisions. We have a growing portfolio of AI–powered products and services and increasing opportunity for re‑use of foundational components through careful design of libraries and services to be leveraged across the team. This role offers a unique blend of scientific research and software engineering, requiring a deep understanding of both mindsets.

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.

We are looking for an outstanding Machine Learning Engineer to help us deliver maximum value on this opportunity.

Job responsibilities

• Build robust Data Science capabilities which can be scaled across multiple business use cases
• Collaborate with software engineering team to design and deploy Machine Learning services that can be integrated with strategic systems
• Research and analyze data sets 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 taking a leading role in the design and delivery of the production architectures for our solutions.
• Act as an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidate’s experience.

Required qualifications, capabilities, and skills

• Masters or PhD in a quantitative discipline, e.g. 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, enhancing existing models over an extended time period
• Extensive experience with PyTorch and related data science Python libraries (e.g. pandas)
• Experience of containerising applications or models for deployment (Docker)
• Experience with one of the major public cloud providers (Azure, AWS, GCP)
• Ability to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders.

Preferred qualifications, capabilities, and skills

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