Applied AI ML - Senior Associate - Machine Learning EngineerJPMorganChase • City of London, England, United Kingdom
Applied AI ML - Senior Associate - Machine Learning Engineer
JPMorganChase
- City of London, England, United Kingdom
- City of London, England, United Kingdom
About
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
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, 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 FAQs for more information about requesting an accommodation.
About the Team J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
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Languages
- English
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