Principal Machine Learning Engineer

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 or 01-