Cloud Software Test Engineer - Custom Object Training (COT), Lund
About this role
Are you an experienced test engineer eager to secure the cloud services that turn AI potential into real-world insights? Do you thrive in a collaborative team and have a passion for Python, test automation, and validating self-service machine learning training pipelines? Our team is looking for a test engineer to help us ensure exceptional quality, scalability, and reliability across our analytics platform.
Who is your future team?
Meet the team behind Custom Object Training (COT): a cutting-edge cloud service that lets customers train cameras to recognize anything they need. We're on a mission to turn complex AI training into a seamless, self-service experience. Bringing this to life is a tight-knit, cross-functional crew of software experts, AI specialists, full-stack developers-and now, you.
Our tech stack is modern and cloud-native: Python is used for the core logic and orchestration, React for the user interface, and modern cloud data services for the data and metadata storage. We view quality as everyone's responsibility, not a siloed task. From code to customer, we build together, own our solutions end-to-end, and champion an environment of fast feedback and continuous growth.
What will you do as a Cloud Software Test Engineer?
Driving test automation and securing our AI training-as-a-service (aaS) platform will be your core mission. Testing a cloud-native machine learning service brings a unique edge: you will master the probabilistic behaviour of ML models while ensuring our self-service workflows, data pipelines, and API contracts remain rock-solid.
Your tasks will include:
Designing, developing, and executing test automation frameworks (primarily using Python) for complex cloud services and AI training workflows.
Testing end-to-end user flows-from data ingestion and model training triggers in the cloud to deployment and validation on edge devices.
Validating data quality and data flows, ensuring our system handles edge cases, sensor noise, anomalies, and