Senior Full Stack Machine Learning Engineer to join our Artificial Intelligence and Machine Learning product area. We are looking for a highly experienced engineer to partner with data engineers and data scientists in delivering AI solutions to automate manual processes.
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.