· Dublin - Hybrid
· Long Term Contract
· Negotiable Day Rate
Senior Full Stack Machine Learning Engineer to join our Artificial Intelligence and Machine Learning product area. The team consists of data engineers and data scientists who partner to deliver AI solutions to automate manual processes with global financial services and investment company.
The Expertise We’re Looking For
• 8+ years hands-on experience working in large-scale, sophisticated systems development initiatives focused on software development, deployment, API development, UI development or similar area
• 3+ years proven hands-on experience using AWS Services especially related to data and analytics, e.g. S3, EC2, Lambda, AWS Step Functions, SNS, SQS.
• Significant experience using CI/CD tools like Jenkins, uDeploy or Concourse.
• Demonstrated experience in deploying data pipeline and OLTP systems in AWS; using platforms like RDS/Postgres and/or data warehousing tools like Snowflake
• Experience establishing 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.
• Strong UI development experience using AngularJS
• Experience maximising tools like EC2 and EKS to run compute for API hosting, ideally on AWS.
• Proven API development experience using Java (Springboot) and/or Python microservices infrastructure and deployment using containerisation (Docker) and container-orchestration systems such as Kubernetes
• Exceptional SQL skills and experience performing complex data analysis on multiple Data Platforms (Snowflake, RDS/Postgres, DynamoDB)
• Significant experience working on AI/ML teams giving you exposure and understanding of the entire machine learning lifecycle.
• Understanding of Model Development and Scoring (inference)
• Strong communication, documentation and presentation skills
• A strong team player who can successfully collaborate with multiple teams 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, Bedrock, Comprehend, Kendra, Cognitive Services, etc.
