Your experience as an ML engineer and your appetite for a new challenge is what we are looking for. The role positions you as a member of our fast paced and integrated group and will be involved in the full end-to-end process through analysis, planning, design, development, quality and implementation of the solutions. It is a dynamic environment requiring strong social skills, superb communication skills, a strong team mentality, superb attention to detail and a sense of ownership.

Experience

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).

Skills

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

To apply or find out more reach out to [email protected] or 01-947 6301