Applied AI ML Lead - Senior Machine Learning Scientist

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Applied AI ML Lead – Senior Machine Learning Scientist, Greater London

Client:

Location:

Greater London, United Kingdom

Job Category:

Other

EU work permit required:

Yes

Job Reference:

abe396ca96a1

Job Views:

6

Posted:

03.03.2025

Expiry Date:

17.04.2025

Job Description:

Applied AI/ML at JPMorgan Corporate Investment Bank combines cutting-edge AI techniques with the company’s vast and unique data assets to optimize business decisions and automate processes. We pride ourselves on being able to rapidly operationalize our solutions. In this role, you will be part of our industry-leading team and advance the state-of-the-art in AI as applied to financial services. You will leverage the latest research from the fields of Natural Language Processing, Computer Vision, and statistical machine learning to build products that automate processes, help experts prioritize their time, and make better decisions.

Our scientists take the lead in translating business requirements into machine learning problems and ensure through ongoing literature review that our solutions leverage the most appropriate algorithms.

Job Responsibilities:

• This role is not a purely academic research role. As an applied team, we are focused on rapidly delivering business value with our solutions.
• Our scientists and engineers collaborate closely throughout the entire product lifecycle to ensure that experimental results are reproducible and we’re able to rapidly promote from “Proof of Concept” to production.
• The role is initially that of an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidate’s experience.

Required Qualifications, Capabilities, and Skills:

• Hands-on experience in a commercial/Postdoctoral Research role.
• Able to understand business objectives and align ML problem definition.
• Track record of solving real-world problems with AI.
• Deep specialization in NLP or Computer Vision.
• Deep understanding of the fundamentals of statistics, optimization, and ML theory.
• Extensive experience with PyTorch, NumPy, and Pandas.
• Hands-on experience fine-tuning modern deep learning architectures (transformers, CNN, autoencoders).
• Knowledge of open-source datasets and benchmarks in NLP or Computer Vision.
• Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders.
• Experience working collaboratively within a team to build software.

Preferred Qualifications, Capabilities, and Skills:

• Experience pretraining foundation models (LLM/vision/multimodal).
• Experience documenting solutions for enterprise risk/governance purposes.
• Hands-on experience in implementing distributed/multi-threaded/scalable applications (including frameworks such as Ray, Horovod, DeepSpeed).
• Experience with big data technologies (e.g., Spark, Hadoop).
• Broad knowledge of MLOps tooling – for versioning, reproducibility, observability, etc.

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