Design, build, and deploy scalable ML services combining NLP, CV, and statistical methods. Collaborate with engineers, cloud and SRE teams to productionize models, ensure observability and compliance, and maintain models over time. Communicate results to stakeholders and document processes for regulatory needs.
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
#CIBAppliedAI
About UsJ.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
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. Visit our FAQs for more information about requesting an accommodation.
Similar Jobs
Financial Services
Design, build, and maintain production-grade AI/ML and agentic systems for the LLM Suite. Write secure, high-quality code, integrate models and services on public cloud (Azure/AWS), collaborate on design and operational reliability, and operationalize agentic patterns like A2A communication and Model Context Protocol.
Top Skills:
Agent-To-Agent CommunicationAgentic FrameworksAgentic OrchestratorsAPIsAWSAws BedrockAzureAzure OpenaiContainerizationElastic ComputeFastapiLanggraphLarge Language ModelsMessaging QueuesMicroservicesModel Context Protocol (Mcp)NoSQLPython
AdTech • Artificial Intelligence • Marketing Tech • Software • Analytics
Lead EMEA programmatic activation, directly managing UK programmatic campaigns and margins, overseeing the France trading lead, setting presales pricing, supporting sales and account growth, troubleshooting ad ops/tracking issues, building a London AdOps team, and partnering on analytics and post-campaign reporting to meet client KPIs.
Top Skills:
Dv360ExcelThe Trade Desk (Ttd)XandrYahoo Dsp
Artificial Intelligence • Fintech • Payments • Business Intelligence • Financial Services • Generative AI
Lead end-to-end market expansion across EMEA and the Middle East: set market-entry strategy, design licensing and operating models, align product roadmap, run cross-functional governance and launch readiness, and support CEO Office strategic initiatives and crisis response.
What you need to know about the Bristol Tech Scene
Along with Gloucester, Swindon and Bath, Bristol is part of the "Silicon Gorge" tech hub, a region in the U.K. renowned for its high-tech and research-driven industries, with a particular emphasis on sustainability and reducing environmental impact. As the European Green Capital, Bristol is home to 25,000 cleantech companies, including Baker Hughes and unicorn Ovo Energy. The city has committed to achieving net-zero emissions within the next decade.
