Software Co-op: Machine Learning Operations Specialist

2 months ago


Vancouver, British Columbia, Canada Sanctuary Cognitive Systems Corp. Full time

About the Role

Sanctuary Cognitive Systems Corp. is seeking a highly skilled and motivated Software Co-op student to join our Data Collection and Machine Learning Operations team. As a key member of our team, you will gain a comprehensive understanding of our data collection pipeline and the process of training, testing, deploying, and optimizing machine learning models that power our humanoid robots.

Key Responsibilities

  • Collaborate with our Data Collection and Machine Learning Operations Lead to design, develop, and deploy machine learning models
  • Work with our simulation and machine learning research teams to enable our robots to learn new skills
  • Participate in the development of our data collection and machine learning pipelines
  • Contribute to the optimization of our machine learning models and deployment processes

Requirements

  • Pursuing or completing a bachelor's degree in computer science or a related technical field
  • Strong programming skills in Python
  • Experience with observability stacks such as Grafana, Splunk, or Datadog
  • Experience with training and deploying machine learning models
  • Familiarity with ML Ops platforms such as Weights & Biases or ClearML
  • Familiarity with robotics (ROS)

Preferred Qualifications

  • Experience with cloud and on-premise systems
  • Knowledge of symbolic logic and reasoning
  • Understanding of multimodal robot foundation models

What We Offer

Sanctuary Cognitive Systems Corp. offers a competitive compensation package, including a market-leading salary, equity stakes, and a full suite of benefits for permanent employees. Our commitment to fairness ensures that our total compensation consistently surpasses market standards.

About Us

Sanctuary Cognitive Systems Corp. is a world leader in building AI-based control systems for humanoid robots. Our mission is to create the world's first human-like intelligence in general-purpose robots. We use our robots to collect vision, audio, touch, and proprioception data from the perspective of the robot while they perform real-world work tasks. We use that data to train multimodal robot foundation models. Because our systems are vertically integrated, we can design, deploy, and refine at scale.



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