DevOps / MLOps Engineer

Ramat-Gan, Tel Aviv District, IL

WSC Sports

WSC Sports is the pioneer in AI-tailored sports content experiences for fans.Connect with your fans through AI-tailored sports content experiences.

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Description

WSC Sports, the pioneer in AI-powered sports content technology, empowers their clients world-wide to connect with their fans through AI-tailored sports content experiences. WSC Sports’ platform automates the creation, management and distribution of content, enabling sports rights holders to expand reach, grow fan bases, and unlock revenue opportunities across digital platforms.

Why WSC Sports:

You'll work in an exciting environment alongside some of the most innovative people in the industry, using cutting-edge tools and technologies. At WSC Sports, you have the opportunity to directly influence the products and solutions used by our clients worldwide, including sports giants such as the NBA, Bundesliga, LaLiga, ESPN - and that's just the beginning of what we have to offer! Join us and be a part of the best tech team as we Fuel The Fandom.

 What you’ll do:

  • Own and manage every aspect in the MLOps life cycle for our AI-based automatic sports highlights generation platform.
  • Design, implement and maintain our whole ML infrastructure, from research to production and from model training to data engineering.
  • Automate and innovate workflows such as serving and training pipelines for multidisciplinary ML algorithms including Computer Vision, NLP and Data Science. 
  • Build and maintain CI/CD pipelines, releases and Source Code workflows.

Requirements

What you’ll need:

  • 4+ years experience as an MLOps engineer, DevOps engineer or similar fields
  • Experience in a complex, large-scale, high-uptime production cloud environment.
  • Core understanding of Linux OS, Docker Components, Kubernetes.
  • Experience with CI/CD pipelines for distributed production systems 
  • Experience with python scripting. 
  • Work experience with Terraform.
  • Understanding of AI and machine learning fundamentals, concepts and frameworks - advantage
  • Working with MLOps platforms such as Experiment Tracking, Model Registry, feature Store - Advantage (e.g ClearML , W&B, Aws Sagemaker)
  • Working with Azure Cloud in high-scale production environment - Advantage
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: AWS Azure CI/CD ClearML Computer Vision DevOps Docker Engineering Kubernetes Linux Machine Learning ML infrastructure MLOps Model training NLP Pipelines Python Research SageMaker Terraform Weights & Biases

Region: Middle East
Country: Israel

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