Summary
Microsoft AI are looking for a talented Member of Technical Staff, Software Engineer to join their MAI SuperIntelligence team in Zürich, Switzerland. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI technology. You'll work directly with leadership to shape the company's direction in the AI market.
About the Role
As a Member of Technical Staff, Software Engineer, you will design and build core platform services for scalable training and evaluation, including cluster orchestration, job scheduling, data and compute pipelines, and artifact management. You will standardize containerized workflows by maintaining Docker images, CI/CD, and runtime configurations; advocate for best practices in security, reproducibility, and cost efficiency. You will implement end-to-end observability and operations through metrics, tracing, logging, dashboard development, monitoring, and automated alerts for model training and platform health (using Prometheus, Grafana, OpenTelemetry). You will architect and operate services on Azure cloud platforms, managing infrastructure-as-code (Terraform/Helm), secrets, networking, and storage. You will enhance developer experience by creating tools, CLIs, and portals that simplify job submission, metrics analysis, and experiment management for generalist software engineering and research teams.
Accountabilities
- Design and build core platform services for scalable training and evaluation, including cluster orchestration, job scheduling, data and compute pipelines, and artifact management.
- Standardize containerized workflows by maintaining Docker images, CI/CD, and runtime configurations; advocate for best practices in security, reproducibility, and cost efficiency.
The Candidate we're looking for
Experience:
- Strong software engineering background building reliable, scalable production systems (Python preferred).
Technical skills:
- Hands-on experience supporting large-scale ML / LLM training, evaluation, or experimentation infrastructure.
- Operating GPU-heavy workloads in cloud environments using Docker and Kubernetes (scheduling, utilization, isolation).
- Designing and running data / compute pipelines and orchestration (e.g., Airflow, Argo) with object storage (Azure Blob / S3).
Personal attributes:
- Building secure, reproducible platforms using CI/CD, infrastructure-as-code (Terraform, Helm), container security, and secrets management.
Benefits
- Competitive salary and benefits package.
- Opportunity to work with a talented team of engineers and researchers.
- Access to cutting-edge technology and resources.
- Flexible work arrangements, including remote work options.
