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Machine Learning Engineer

Ref: 15208649

Posted on 09 November 2022
Job Location
Contract Type


  • Build machine learning solutions with global impact, helping Nike’s business and consumers
  • Work end-to-end on the ML lifecycle, from data exploration to model operationalization
  • Collaborate with data engineers, data scientist, product etc in a multi-functional team to the delivery and maintenance of these solutions and business integration
  • Partner with different teams and domains on designing, explaining and implementing ML models
  • Play and active role in the research and innovation w.r.t. the applicability of ML to improve business objectives
  • Participate in the design and execution of A/B testing, model competition etc.
  • You will be responsible for, and support users with the solutions that you and the team has built
  • Work with the MLOps engineer in your team on different the operationalization fo the models, which can be batch inference, or live through providing API’s
  • Integrate your models with Nike’s systems or make them consumer facing through the mobile Apps or
  • Ensure high quality solutions are delivered, through testing, applying engineering standards and actively working on model monitoring


Akkodis is a worldwide market leader in the field of HR Solutions that deliver agile end-to-end solutions for our customers, including professional staffing and consulting, project services, managed services, customized solutions, and outsourcing projects.

At Akkodis IT you are given the opportunity to grow continuously as an expert within your specialist field. We exist to connect the smartest people and brightest businesses to the opportunities they need to thrive.


• 5+ years of experience working with Machine Learning, and delivering business value through applying ML
  • Advanced degree in computer science, math, statistics, engineering or a related degree
  • Experience with Python, ML libraries (such as scikit-learn, pytorch, etc), SQL, Spark, pandas and cloud technologies
  • Thorough understanding of applied statistics, both shallow and deep ML models, can clearly articulate model choice trade-offs, neural network architecture and performance metrics
  • Experience in designing and running live model tests such as through A/B or multi-armed bandit testing
  • Have strong knowledge of the whole model lifecycle from exploring data to bringing machine learning solutions to production and integrating within Nike
  • Experience with containerizing ML workloads, using docker and kubernetes
  • Background in software engineering, and experience with CI/CD, testing & creating microservices is highly preferred

Do you have a question for us? Or are you looking for more information? Please let us know. 

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