Senior Machine Learning Engineer - Data Analytics AI Engineering (VP, Vice President)

JP Morgan

Location: Greater London

Job Type: Full time

Posted


About Data Analytics at J.P. Morgan CIB

Data Analytics at JPMorgan Corporate Investment Bank combines cutting edge machine learning techniques with the company’s unique data assets to optimize all the business decisions we make. We strive to be leaders in technological innovation by deploying cutting-edge AI techniques and driving the first adoption of strategic cloud platforms. At the same time, culture matters to us and we have worked hard to foster a community amongst all AI and ML practitioners firm-wide to promote sharing, collaboration, learning and, fun.

In this role, you will be part of our industry-leading data analytics team, and advance the state-of-the-art in AI as applied to financial services. You will leverage the latest research from fields of NLP, computer vision and statistical machine learning to build products that automate process, help experts better prioritize their time and make decisions. This is a position within the firm’s Applied AI and Machine Learning organization and will involve working closely with CIB Operations.

Job Description

We have a growing portfolio of AI – powered products and services that is creating increasing opportunity for re-use of foundational components through careful design of easily accessible libraries and services that can be leveraged across the team.

We are looking for an outstanding Senior Machine Learning Engineer to help us deliver maximum value on this opportunity.

This role straddles the boundary between data science and software engineering and requires a deep understanding of both mindsets.

The candidate must have a proven track record of superior problem-solving and system design skills through previous experience in delivering AI/ML infused products using cloud infrastructures (AWS, Azure or GCP).

The role is initially that of an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidates preference/ experience.

Qualifications / Experience / Knowledge - Required

  • Considerable experience in an ML engineering role
  • PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics
  • Track record of developing, deploying business critical machine learning models
  • Experience monitoring, maintaining, enhancing existing models over an extended time period
  • Deep understanding of statistics, optimization and ML theory
  • Extensive experience with PyTorch and/or Tensorflow
  • Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.)
  • Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.)
  • Able to understand business objectives and ensure ML problem definition is aligned
  • Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders
  • Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc
  • Excellent grasp of comp sci fundamentals and dev best practice

Qualifications / Experience / Knowledge – Desirable

  • 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
You’ve got this!