You will own and deliver end-to-end computer vision projects for power grid analysis, including defect detection and vegetation monitoring.
You will bridge research and production by reading papers, adapting algorithms, and deploying reliable models.
You will work within a team of experienced ML engineers with the autonomy to drive your own projects.
Buzz uses advanced AI to analyze and maintain power grid infrastructure, enhancing safety and efficiency. The team consists of experienced ML engineers who work autonomously and support each other's growth.
Assist in developing computer vision models for wildfire detection and environmental monitoring.
Help implement and maintain ML/CV pipelines and deploy models on NVIDIA Jetson edge platforms.
Collaborate with AI researchers, software engineers, and product teams to optimize and document solutions.
Pano AI is the leader in AI-powered wildfire detection and intelligence, helping fire professionals detect, respond to, and contain wildfires faster and more safely. We are a team of more than 175 people working in a hybrid-remote environment across North America and Australia, with headquarters in San Francisco.
Design, develop, and optimize computer vision models and deep learning capabilities across the product portfolio.
Build and maintain ETL pipelines, clean datasets, and perform feature engineering for machine learning applications.
Collaborate with cross-functional teams to productionize, deploy, and monitor models in real-world environments.
FloVision is a remote-first startup improving the food supply chain with computer vision and ML. It is a Series A company with a distributed team across the US, UK, and Ireland.
Own tracking and reporting of CV accuracy metrics, investigating misclassifications and identifying patterns across customers.
Curate, label, and prioritize datasets for model retraining, partnering closely with ML and CV engineers.
Build and improve the continuous learning pipeline, moving from flagging issues to fixing them directly.
We are building the backbone of freight by reinventing supply chain infrastructure with carrier agnostic truck terminals. We are a vertically integrated real estate, operations, and technology company backed by $1B, scaling to build the most valuable logistics network in the country, with a culture of accountability, integrity, and high performance.
Experiment with modern neural network architectures and techniques driven by research
Design and implement machine learning perception solutions in new domains
Collaborate with AI Data Team, ML engineers, and Cloud infrastructure engineers
AMP applies AI-powered sortation to modernize recycling infrastructure and maximize waste value. Recognized as a top workplace in Colorado, AMP has hundreds of global deployments and is backed by top-tier investors.
Support training, fine-tuning, and evaluation of neural foundation models.
Build and maintain data pipelines for petascale neurobehavioural datasets.
Prototype tools and demos to apply trained models to robotics and embodied AI tasks.
Netholabs builds AI grounded in biological intelligence by recording petascale neurobehavioural data to train neural foundation models. They are a small, fast-moving research team focused on AI, robotics, and personalized intelligence.