Applied AI ML - Senior Associate - Machine Learning Engineer

Testing Site - JPMC; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

JPMorgan Commercial & Investment Bank is seeking an Applied AI / ML Senior Associate Machine Learning Engineer in its Applied AI ML team. The role combines cutting-edge AI techniques with the bank's data assets to optimize decisions and automate processes, leveraging NLP, CV, and statistical ML.

You will build products to automate tasks, help experts prioritize work, and enable re-use of foundational components across teams.

Qualifications

• Master's or PhD in a quantitative field is required.
• Strong grounding in statistics, optimization and ML theory.
• Research or practical NLP focus is preferred.
• Experience with MLOps tools for versioning and observability.
• Proven track record maintaining models over time.
• Proficient with PyTorch and Python (pandas).
• Containerization with Docker; cloud experience (Azure/AWS/GCP).
• Ability to explain technical concepts to diverse audiences.

Responsibilities

• Build scalable data science capabilities across use cases.
• Collaborate with software engineers to deploy ML services.
• Research data sets using statistical and ML methods.
• Communicate AI capabilities and results to technical and non-technical audiences.
• Document approaches and processes to satisfy industry regs.
• Work with cloud and SRE teams on production architectures.
• Potential for management responsibilities depending on experience.

Skills

Statistics fundamentals

ML theory

NLP

MLOps tooling

Model monitoring

PyTorch

Python (pandas)

Docker

Cloud platforms (Azure/AWS/GCP)

Communication with stakeholders

Education

Masters or PhD in CS/Math/Statistics

Tools

Kubeflow

DVC

Ray

Docker

Kubernetes

Helm

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.

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 analyse 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

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