Machine Learning Ops Engineer

We are looking for an excellent ML Ops Engineer to join our research and development team.

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• This opportunity is to join the ML Operations teams which supports the ML Development team in building leading-edge motion capture products through provisioning and maintaining a modern ML Operations stack.
  
• This stack covers data acquisition pipelines, data management and ML model training infrastructure (SW and on-prem HW). We use both on-prem, self-managed systems and also leverage AWS infrastructure.
  
• You will have opportunities to guide the technical direction of the ML Ops team, suggest new areas of development and the potential to lead your own project.
  

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• You will have relevant academic (research Masters level) and/or industry experience.
  
• Excellent knowledge and experience of managing an on-premise Kubernetes cluster.
  
• Excellent knowledge of Kubeflow and similar systems, e.g. MLflow.
  
• Good programming ability in Python with familiarity with Linux systems including scripting and system configuration.
  
• Experience using AWS, e.g. Cognito, S3, EC2, Lambda, etc.
  
• Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools.
  
• Be able to design and implement MLOps solutions covering many different technologies.
  

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• Background in DevOps with exposure to CI systems, e.g. Jenkins.
  
• Familiarity with infrastructure as code, e.g. Ansible.
  
• Experience, aptitude, and a desire to work with human motion, sport, animation tools and techniques.
  
• Familiarity with C.