Staff ML/OR Engineer: Dispatch AI Leader – Remote in Winnipeg

Staff ML/OR Engineer: Dispatch AI Leader – Remote in Winnipeg

Winnipeg Full-Time 135000 - 165000 $ / year (est.) Remote
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At a Glance

  • Tasks: Lead the development of AI models that enhance delivery systems and drive revenue.
  • Company: Burq, a forward-thinking tech company focused on innovation.
  • Benefits: Fully remote work, competitive salary, and opportunities for professional growth.
  • Other info: Join a dynamic team tackling complex challenges in a supportive environment.
  • Why this job: Make a real impact in AI and optimization while working with a global team.
  • Qualifications: Experience in machine learning and operations research is essential.

The predicted salary is between 135000 - 165000 $ per year.

Burq is hiring a Staff ML/OR engineer to define the intelligence at the core of Dispatch OS.

You will own the architecture for ML and optimization, steer the roadmap, and build high‑leverage models that impact revenue and delivery reliability.

You will lead hardest problems, collaborate across Engineering and Data, and set production ML standards while delivering scalable, auditable solutions in a fully remote global team.

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Staff ML/OR Engineer: Dispatch AI Leader – Remote in Winnipeg employer: Tandem Inc.

Burq is an exceptional employer that fosters a culture of innovation and collaboration, allowing employees to make a significant impact while working on meaningful projects. With generous time off and a fully remote work environment, Burq prioritizes employee well-being and growth, empowering team members to leverage cutting-edge AI tools in their daily tasks. Join us to be part of a world-class team backed by leading Silicon Valley investors, where your contributions will help redefine the future of logistics.

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Contact Details:

Tandem Inc. Recruitment Team

We think you need these skills to ace Staff ML/OR Engineer: Dispatch AI Leader – Remote in Winnipeg

Machine Learning
Optimization
Architecture Design
Roadmap Development
Model Building
Revenue Impact Analysis
Delivery Reliability Improvement