- Provide the software engineering and best practices required around the production of an AI model application from start to finish
- Bring the team’s AI models to life by working with Engineering and Product teams to develop real-time customer-facing products which are empowered by the models
- Build integration between model serving endpoints with front-end web and mobile applications and other services that consume the model output
- Integration between the model training/inference jobs and databases, including real-time data streams
- Prove values of the AI team’s work to the business by being able to quickly build POCs and prototypes to demonstrate
- Build scalable live A/B testing architecture and implementation around model deployment so that we can rapidly and continuously experiment new models.
- Collaborate with Data Scientists and other Engineering teams to build the AI platform capabilities that enables us to deliver the above through efficient model training, deployment and CI/CD pipelines
- Support what AI team build, implement robust testing, monitoring, logging and alert
- Work in a global and cross-functional team, play the role of a thought leader and an engineering expert to help shape the design and production of future Pepperstone products
Closed
AI Engineer
Date Posted: 18-10-2022
Level: Senior Level
Our AI engineers are responsible for transforming the AI models from conceptualisation and development stages into products and features in Pepperstone’s trading frontends.
Responsibilities
Qualifications
- 2+ years building and deploying applications using one or more AWS cloud technologies
- AI/ML pipelines on AWS Sagemaker and other pipeline orchestration tools such as MLFlow, Apache Airflow, Kubeflow etc...
- Data Engineering and DevOps skills in automation (e.g. CI/CD tool such as Github action, BuildKite; infra as code such as Terraform, CloudFormation) and virtualisation (e.g. Docker, Kubernetes) related to model deployment and scaling
- Engineering experience related to designing APIs & microservices, integration among AWS databases
- Familiarity with different microservice deployment methodologies, including A/B testing, bluegreen and canary deployments is a plus
- Proficient in Python or other programming languages used for developing AI/ML models
- A commitment to ongoing learning & development
Desirable:
- Full-stack engineering experience with backend services and frontend web & apps on Cloud is a plus
- Experience building AI/ML-driven customer-facing products in a fast-moving B2C e-commerce or market place environment
- Experience working with real-time data streams, Feature Store and/or Data Lake
- Relevant knowledge in one or a few areas of AI, Machine Learning, algorithms, statistics, optimizations, hypothesis testing
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