Role overview

Qualifications

7-10 years of industry experience in computer vision and machine learning
Deep expertise in modern computer vision and deep neural networks including object detection, semantic segmentation, image classification, similarity search, and vision-language models
Proven track record deploying and maintaining ML models in production
2-3 years of proven leadership experience of technical teams

Responsibilities

Architect and lead end-to-end computer vision projects for power grid applications, including equipment defect detection, thermal anomaly identification, vegetation encroachment monitoring, and surveillance of restricted areas
Drive innovation by applying state-of-the-art deep learning and generative AI to improve training, accuracy, and reliability of models
Develop production-grade Python libraries to support the full ML lifecycle, including deployment and monitoring
Mentor teammates and establish best practices for model development, evaluation, deployment, monitoring, and uphold software quality standards within the ML team

About the company

Buzz Solutions

Utilities (Electric, gas & water)

Buzz Solutions provides a platform for teams to manage and analyze data, collaborate, and export inspection results, fostering smart, stable, and resilient infrastructure inspections. We automate the process of infrastructure inspections for faults and anomalies by analyzing millions of visual data points captured by helicopters, drones and linemen in the field. Using our solution, our customers are saving immense time and money as a part of their inspections, while drastically improving the efficiency of their infrastructure inspections.

Company details

Company typeStartup

IndustryUtilities (Electric, gas & water)

Company size11 - 50

Links

Website LinkedIn See all jobs

Your match analysis

See how your profile stacks up against this role.

We compared the job requirements to your profile to show where you're strong and where you fall short.

Job description

Job Description

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 seeking an experienced Machine Learning Engineer to help lead our computer vision initiatives. You'll drive the development of cutting-edge models for power grid analysis and provide a leadership anchor on a team of talented ML engineers.

Responsibilities

Architect and lead 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 intrusions
Drive innovation by incorporating the latest advances in deep learning and generative AI to enhance model training, accuracy and reliability
Develop production-grade Python libraries for the complete ML lifecycle
Mentor team members and establish best practices for model development, evaluation, deployment, and monitoring
Advocate for and uphold software quality standards within the ML team

Qualifications & Experience

7-10 years of industry experience in computer vision and machine learning
Deep expertise in modern computer vision and deep neural networks including: Object detection, Semantic segmentation, Image classification, Similarity search, Vision language models
Proven track record of deploying and maintaining ML models in production
Expert proficiency in PyTorch, Lightning, OpenCV, and Scikit-Learn
Proficiency in FastAPI and Pydantic
Strong software engineering foundation including: Git version control, Test driven development (Pytest), CI/CD, ML devops, Python type hinting
2-3 years of proven leadership experience of technical teams

Desired Additional Experience

Multi-modal computer vision
Custom object detection model development
Generative models for data augmentation
ML deployment on edge devices
Extracting measurements from GIS and/or drone metadata enriched imagery
Model quantization
Systematic hyperparameter tuning

Additional information:

This position does not include sponsorship for United States work authorization.