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JPMorgan Applied AI ML - Sr Associate Machine Learning Engineer 
United Kingdom, England, London 
700455950

26.06.2024

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
  • 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
  • Extensive experience with pytorch, numpy, pandas
  • Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.)
  • Excellent grasp of comp sci fundamentals and dev best practice
  • 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)
  • Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.)
  • Knowledge of open source datasets and benchmarks in NLP / Computer Vision
  • Have constructed batch and streaming microservices exposed as REST/gRPC endpoints
  • Familiarity with GraphQL