AWS Machine Learning Architect

3 days ago


London, Greater London, United Kingdom DraftKings Full time

We are seeking an experienced AWS Machine Learning Architect to join our team at DraftKings. The ideal candidate will have experience designing and deploying scalable machine learning solutions using AWS services such as SageMaker, Rekognition, and Comprehend.

As a member of our global team, you will be responsible for building and delivering the most extraordinary sports and entertainment experiences. You will work closely with cross-functional teams to design and deploy innovative DS products that deliver incremental value on the Sportsbook platform.

Key Responsibilities:

  • Design and deploy scalable machine learning solutions using AWS services such as SageMaker, Rekognition, and Comprehend
  • Collaborate closely with product, developers, QAs and delivery leads to move projects from ideation to development and deployment
  • Develop and maintain high-quality machine learning models and integrate them into DS applications
  • Work with and help develop our MLOps pipeline
  • Data engineering of data assets to assist in DS application development
  • Writing production quality code to deploy and run models in a sportsbook
  • Create automatic tests to ensure accuracy and reliability of DS applications
  • Test that data flows work as expected and that DS applications are well integrated in larger business context
  • Build advanced analytics tools for sportsbook product teams
  • Couch and support more junior data scientists within the team

Requirements:

  • PhD, Masters or Bachelor's degree in STEM fields
  • Highly proficient in at least one programming language, ideally Python, with a strong understanding of object-oriented programming principles
  • Understanding of different database technologies, including relational and non-relational databases
  • Experience implementing ML automation, MLOps principles and related tools
  • AWS experience will be considered an asset
  • Experience with typical DevOps flows, such as containerisation (e.g. Docker) and monitoring (e.g. ELK, Grafana)
  • Experience with Kubernetes and Kafka are very desirable
  • Knowledge of web frameworks (e.g. Flask, Django) and HTTP APIs desirable
  • Keen interest in sports
  • Understanding of Sportsbook products will be considered an asset
  • Experience leading and coaching other data scientists
  • Excellent communication & organization skills with the ability to articulate key business information quickly and effectively

Estimated Salary: $160,000 - $210,000 per year



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