Backed by Stanford.
About the role
We're looking for a Machine Learning Engineer to advance our computer vision initiatives and help build our foundational model capabilities. You'll bridge the gap between cutting-edge research and production systems , reading papers, adapting novel algorithms, and turning them into reliable, deployed models for power grid analysis. You'll work within a team of experienced ML engineers, with the autonomy to drive your own projects and the support to keep growing.
What they're looking for
- 2-5 years of industry experience in computer vision and machine learning
- Solid understanding in modern computer vision and deep neural networks, including:
- Semantic segmentation
- Image classification
- Vision transformers and foundation models
- Vision language models
More about this role
Buzz is revolutionizing the analytics and maintenance of power grid infrastructure through our advanced AI solutions. Our computer vision systems analyze critical infrastructure to enhance safety, reliability, and operational efficiency across the power grid network.
We're looking for a Machine Learning Engineer to advance our computer vision initiatives and help build our foundational model capabilities. You'll bridge the gap between cutting-edge research and production systems , reading papers, adapting novel algorithms, and turning them into reliable, deployed models for power grid analysis. You'll work within a team of experienced ML engineers, with the autonomy to drive your own projects and the support to keep growing.
Project delivery
- Own and deliver end-to-end computer vision projects focused on:
Equipment defect detection
- Thermal anomaly identification
- Vegetation encroachment monitoring
- Surveillance of closed areas for human and animal intrusion
- Scope, plan, and execute your own projects from problem framing through production deployment and monitoring.
- Deliver on client projects, translating client requirements and raw data into working computer vision...
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