> Markdown version of [/jobs/ext/2258754-applied-ai-ml-senior-associate-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/2258754-applied-ai-ml-senior-associate-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Applied AI ML - Senior Associate - Machine Learning Engineer - **Company:** JPMorgan Chase & Co. - **Location:** London, UK - **Experience:** Expert - **Salary:** £83,309.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Directed Acyclic Graph (Directed Graphs), Python (Programming Language), Machine Learning, Open Source Technology, Software Engineering, Data Streaming, Management of Software Versions, Multithreading, Google Cloud, Pytorch, Deep Learning, Pandas, Kubernetes, Information Technology, Machine Learning Operations, Artificial Intelligence Markup Language (AIML), Docker, Microservices - **Published:** August 26, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5854688012 ## About the Role * 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 ## Description Join a high performing team of applied AI experts to drive innovation and new capabilities in the Commercial & Investment Bank., * 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. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Got AI ideas but no money? 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