Senior AI/ML Engineer

3 weeks ago

London, Greater London, United Kingdom https:jobs-redefined.cositemap Full time

As a Senior AI/ML Engineer in the Applied AI/ML team at JPMorgan Corporate 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.

Key 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.

This role is initially that of an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidate's experience.

Requirements:

  • Hands on 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.
  • Specialism in NLP or Computer Vision.
  • Solid understanding of fundamentals of statistics, optimization and ML theory.
  • Knowledge of open source datasets and benchmarks in NLP/Computer Vision.
  • Experience of big data technologies.

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