Machine Learning Ops Developer
On-site · Toronto, Ontario, Canada
Job Summary
Machine Learning Ops Developer needed to operationalize Autodesk's AI/ML Platform. Responsibilities include designing and implementing automated deployment pipelines for ML models, building scalable infrastructure for model training, inference, and data processing, and maintaining robust monitoring and logging to track model performance and platform health. The role collaborates with data engineers to ensure efficient data pipelines, enforces model governance and version control, and upholds security and compliance standards. Strong emphasis on automating processes, troubleshooting operational issues, and partnering with cross-functional teams (data engineers, software developers, researchers) to improve the MLOps lifecycle. Requirements include 3+ years in DevOps/MLOps, IaC (Terraform/Ansible), containerization (Docker/Kubernetes), CI/CD for ML projects, Python/Bash scripting, and experience with monitoring (Prometheus, Grafana, ELK), plus knowledge of security best practices and collaboration across disciplines.
Required Qualifications
- BS or MS in Computer Science, or related field
- 3+ years of hands-on experience in DevOps and MLOps, deploying and managing ML models in production
- Infrastructure as Code (Terraform or Ansible)
- Containerization (Docker, Kubernetes)
- CI/CD pipelines for ML projects
- Scripting in Python, Bash, or similar
- Monitoring tools (Prometheus, Grafana, ELK Stack)
- Security best practices in MLOps (encryption, access controls, compliance)
- Collaboration skills across data engineers, software developers, and researchers
- Problem-solving in operational issues
Apply with one swipe on Sorce. We auto-fill applications and apply on your behalf — no cover letters, no 40-minute forms.
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.