DevOps (AI/ML) 37482

  • Start date: ASAP
  • Duration: 11 months
  • Location: 1 week in office and 3 weeks from home - 1 Waterside, Kingswood Ave, Dublin Ireland
  • Rate: €450 - €500 per day

The Experience We're Looking For
  • You will utilise your experience working in large-scale, sophisticated systems development initiatives.
  • Significant experience working on AI/ML teams giving you exposure and understanding of the entire machine learning lifecycle.
  • Experience using CI/CD tools like Jenkins, uDeploy or Concourse to establish CI/CD pipelines to deploy code and services to AWS preferably (or similar Cloud Provider), familiarity with IAM roles and policies and other security related artefacts, certificates etc…
  • Hands-on experience using AWS Services especially related to data and analytics - S3, EC2, Lambda, Glue, SNS, SQS for example
  • Demonstrated experience in deploying data pipeline and OLTP systems in AWS; using platforms like RDS/Postgres and/or data warehousing tools like Snowflake
  • Experience maximising tools like EC2 and EKS to run compute for API hosting on AWS ideally
  • Hands-on experience in assisting with (EDA) and feature engineering, Deployment, Tuning, Monitoring, Measurement and Retraining using ML infrastructure and MLOps in the Cloud (AWS preferred).
The Skills You Bring
  • A dedication to your craft and experience in software development, deployment, API development and UI development
  • Exceptional SQL skills and experience performing complex data analysis on multiple Data Platforms (Snowflake, RDS/Postgres, DynamoDB)
  • Working with Orchestration/DAGS tools (Airflow, Prefect, Luigi, Kubeflow or equivalent)
  • API development using Java (Springboot) and/or Python microservices infrastructure and deployment using containerisation (Docker) and container-orchestration systems such as Kubernetes
  • Your understanding of Model Development and Scoring (inference)
  • Your technical leadership skills and ability to communicate with a highly diverse peer group, both verbally and in written communications.
  • Your leadership skills, which enable you to lead several projects concurrently, collaborating with multiple teams and coordinating dependencies to deliver high quality AI/ML solutions.
Nice to have or have an interest in learning;
  • Experience with Cloud service provider ML ecosystem such as AWS SageMaker, Azure ML and MLOps platform such as MLFlow, ModelOp, Seldon or equivalent
  • Experience with AWS and Azure AI ecosystems such as Textract, Comprehend, Kendra, Cognitive Services, etc