Staff MLOps Engineer

📋 Description

• Work collaboratively with partner ML and annotation engineers, as well as TPMs, to define infrastructure and training requirements.

• Create and uphold efficient CI/CD and Continuous Training (CT) pipelines for intricate multimodal models.

• Develop and implement versioning and storage strategies for extensive 2D/3D datasets to guarantee reproducibility and high-throughput access.

• Set up and manage systems that monitor model performance and identify data drift in production settings.

⛳️ Requirements

• Possess a graduate degree (Master's or PhD) in Computer Science, Software Engineering, or a related discipline.

• Have over 5 years of experience as an MLOps Engineer in dynamic applied machine learning settings.

• Demonstrate proficiency in Python, Git, and the Unix shell.

• Exhibit deep familiarity with Docker, Kubernetes, and workflow orchestrators (e.g., Airflow, Prefect, or Kubeflow).

• Have experience with collaborative tools such as Jira/Confluence, Slack, and a Git server.

• A strong mathematical foundation is preferred for understanding the resource needs of 3D data transformations.

• Show high attention to detail regarding system reliability and data security.

• Ability to convert abstract ML requirements into tangible, scalable cloud or on-premises infrastructure.

• Previous experience collaborating with complex multidisciplinary teams (e.g., robotics, smart grids, precision agriculture, game development, or aerospace).

• Must be legally authorized to work in Canada.

🏝️ Benefits

• Health insurance

• Retirement plans

• Paid time off

• Flexible work arrangements

• Professional development