Machine Learning Operations

2 weeks ago

Canada Altis Recruitment Full time

About the Role

We are looking for a Machine Learning Operations (MLOps) Engineer specializing in data labeling workflows to support and optimize our annotation pipeline . This role will be responsible for troubleshooting platform issues, automating annotation processes, and managing API integrations to ensure high-quality labeled data for machine learning models. The ideal candidate has strong Python development skills, experience with data annotation tools (e.g., Labelbox, Scale AI, CVAT), and a passion for optimizing ML workflows .

Key Responsibilities

Platform Support & Troubleshooting

  • Act as the technical lead for data annotation tools such as Labelbox, Scale AI, CVAT , and others.
  • Monitor support channels , troubleshoot platform issues, and ensure smooth annotation workflows.
  • Work closely with ML engineers, data scientists, and annotation teams to resolve integration challenges.
  • Manage onboarding & access for internal teams using the annotation platform's QA environment.

Automation & Development

  • Develop and maintain Python scripts to optimize data labeling pipelines and reduce manual work .
  • Build automation tools for data ingestion, annotation, and transformation .
  • Ensure seamless SDK & API integrations between the annotation platform and internal ML workflows.
  • Implement updates to SDK versions and support new platform feature releases.

Process Optimization & Documentation

  • Identify and execute opportunities to streamline data launch and download processes .
  • Improve annotation workflow efficiency , ensuring faster turnaround times .
  • Create and maintain technical documentation for troubleshooting, workflows, and best practices.

Required Qualifications

3+ years of Python development experience , with a focus on SDKs, REST APIs, and automation .

Experience working with data labeling tools (e.g., Labelbox, Scale AI, CVAT, Amazon SageMaker Ground Truth ).

Strong background in data pipeline development, ingestion, and dataset management .

Ability to debug and troubleshoot automation failures in data annotation workflows .

Experience working in MLOps, data engineering, or machine learning data workflows .

Strong communication skills and ability to work in a cross-functional environment .

Preferred Qualifications

Experience with Apache Airflow for data pipeline automation.

Familiarity with JavaScript and frontend development tools for UI optimizations.

Background in quality control and annotation process improvements .

Experience integrating multiple data annotation platforms into ML pipelines.

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