About the role
Machine learning infrastructure underpins all of our data products, and enables R&D on highly complex systems with the potential to unlock untapped value. We are looking for a Senior Machine Learning Infrastructure Engineer who can scale our market-leading behaviour models, enable the execution of scientific endeavors in a deep-learning dominant environment, and extend the way we apply machine learning to all areas of the business. We’re looking for people who are hungry to make an impact, are comfortable in a fast-paced environment, and love helping the people around them succeed.
We are looking for a Senior Machine Learning Infrastructure Engineer who can scale our market-leading behaviour models, grow our team of data scientists, and extend the way we apply machine learning to all areas of the business. We’re looking for people who are hungry to make an impact, are comfortable in a fast-paced environment, and love helping the people around them succeed.
What your day could look like
Design and maintain scalable ML pipelines for training, validation, and inferenceBuild and optimize model serving infrastructure with proper monitoring, logging, and alertingImplement MLOps practices including automated testing, deployment, and rollback systemsManage data pipelines and ensure data quality, lineage, and governanceOptimize model performance and resource utilization across different environmentsCollaborate with data scientists to productionize models and research experimentsTechnical Requirements:
Strong proficiency in cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)Experience with ML frameworks (TensorFlow, PyTorch) and serving systemsKnowledge of orchestration toolsProficiency in Python, SQL, and Infrastructure as Code (Terraform)Experience with monitoring and observability toolsUnderstanding of CI/CD pipelines and version control systemsInfrastructure Skills:
Database management (both SQL and NoSQL) and data warehousing solutionsStream processing and real-time data systems (Kafka, Spark Streaming)Model registry and experiment tracking systemsPerformance optimization and cost management in cloud environments
What we’re looking for
A comprehensive understanding of the fundamentals and design systems behind building reliable, scalable and fit-for-purpose machine learning models and infrastructureStrong experience in Python and familiarity with development in a backend tech stackA strong understanding of data engineering best practices and AWS infrastructureA confident understanding of data engineering best practices and AWS infrastructureImportantly, we are looking for someone who is passionate about what they do and eager to learn
