Key skills
AzureCloudDistributed SystemsKubernetesMicroservicesPythonAIMLMLOpsCI/CD
About this role
Role Overview
- Design and build scalable AI platform services using Python and microservice architectures
- Own DevOps and MLOps workflows including CI/CD, model deployment, versioning, and rollback
- Build and maintain Kubernetes-based platforms for AI workloads
- Work on data pipelines, dataset versioning, and auto-labeling workflows for model training
- Enable end-to-end ML lifecycle: data ingestion, training, evaluation, deployment, and monitoring
- Collaborate closely with ML researchers, product teams, and other platform engineers
- Drive best practices in software design, reliability, security, and observability
- Lead technical discussions, review designs, and mentor team members
Requirements
- 10+ years of experience in backend or platform engineering
- Strong proficiency in Python (or similar backend languages)
- Solid experience building microservices and distributed systems
- Hands-on expertise with Kubernetes in production environments
- Strong understanding of DevOps and MLOps principles
- Experience with data management for ML (datasets, labeling, pipelines)
- Cloud experience with Azure or strong willingness to adopt Azure quickly
- Ability to think at system level and still deliver hands-on
Tech Stack
- Azure
- Cloud
- Distributed Systems
- Kubernetes
- Microservices
- Python
Benefits
- We provide remote and hybrid working options to fit all lifestyles.
- We use flexible hours across most of our teams to allow you to find your own definition of balance.
- Encouraging a culture of giving, we provide two paid volunteering days off every year so you can take time to contribute to the causes you care about.
- To ensure your family is cared for, we offer paid parental leave in all our locations.