Applied AI ML Lead - DocAI

Next Frontier Capital

Greater London

On-site

GBP 120,000 - 180,000

Full time

14 days+
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Job summary

JPMorgan Chase & Co. is seeking an Applied AI / ML Lead – Vice President to drive ML engineering across strategic teams. You’ll combine NLP, CV, and statistical ML to automate decisions and scale data-driven intelligence.

You’ll lead design of scalable ML services, collaborate with software engineers and SRE, and contribute to production-grade architectures while advancing state-of-the-art research in financial applications.

Qualifications

  • Hands-on experience in an ML engineering role.
  • Masters degree or PhD in a quantitative field.
  • Proven record deploying business-critical ML models.
  • Broad knowledge of MLOps tooling for versioning and observability.
  • Experience monitoring and enhancing models over time.
  • Specialism in NLP or Computer Vision.

Responsibilities

  • Build robust Data Science capabilities scalable across use cases.
  • Collaborate with software engineering to design and deploy ML services.
  • Research and analyse data sets using statistical and ML techniques.
  • Communicate AI capabilities to technical and non-technical audiences.
  • Document approaches to comply with industry regulation.
  • Collaborate with cloud and SRE on production architectures.

Skills

ML engineering
Advanced degree
Model deployment
MLOps tooling
Model monitoring
NLP or CV
Statistics & ML theory
PyTorch / NumPy / Pandas
Distributed systems
Technical communication

Education

Masters or PhD in quantitative discipline

Tools

PyTorch
NumPy
Pandas
Ray
Horovod
DeepSpeed

Job description

Take a technical leadership position within JPMorgan's Commercial & Investment Bank, where you'll harness cutting-edge AI techniques to revolutionize business decisions and automate processes.

As an Applied AI / ML Lead – Vice President - 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. The role is initially that of an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidate’s experience.

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
Required qualifications, capabilities, and skills
  • Hands on experience in an ML engineering role
  • Masters degree or PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics
  • Track record of developing, deploying business critical machine learning models
  • Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc
  • Experience monitoring, maintaining, enhancing existing models over an extended time period
  • Specialism in NLP or Computer Vision
  • Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.)
  • Extensive experience with pytorch, numpy, pandas
  • Hands‑on experience in implementing distributed/multi‑threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.)
  • Able 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 (e.g. Spark, Hadoop)
  • Have constructed batch and streaming microservices exposed as REST/gRPC endpoints
  • Familiarity with GraphQL

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.

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