Easy Apply
Easy Apply
Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.
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.
Top Skills
Fastapi
Opencv
Pydantic
Python
PyTorch
Scikit-Learn
Similar Jobs
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Generative AI
As a Senior Open-Source ML Engineer, you will enhance computer vision tools, optimize models for production, mentor others, and collaborate with the community to democratize AI.
Top Skills:
DatasetsDetectron2MmdetectionOpencvPythonPyTorchTensorFlowTransformers
Computer Vision • Healthtech • Information Technology • Logistics • Machine Learning • Software • Manufacturing
The role involves building computer vision models, researching deep learning methods, handling large datasets, and implementing MLOps best practices.
Top Skills:
3D Deep LearningComputer VisionPythonPyTorch
Transportation
Design and deploy deep learning models for autonomous rail vehicles, focusing on machine learning and computer vision challenges. Collaborate with cross-functional teams to integrate ML into real-world applications.
Top Skills:
CudaNumpyPandasPythonPyTorchScipyTensorFlowTensorrt
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
