Sr. Machine Learning Engineer - Computer Vision and Geospatial Analytics

Buzz Solutions
San Francisco, California, US
Closing date
Oct 31, 2021

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Buzz Solutions safeguards the world's energy infrastructure by providing AI-based actionable insights and predictive analytics for power line and energy infrastructure inspections.

We are disrupting the power utility industry by providing automation for inspection and maintenance operations for infrastructure, using our AI-powered software platform, and are a venture backed and funded startup looking for great talent to share our vision of energy industry transformation.

Our solutions and technology allows the utilities to reduce current inspection operation costs by at least 50%, prevent power outages, prevent wildfires and manage their assets in an effective way.

You will be working with a talented, passionate and hardworking team of engineers and product managers to build end-to-end Machine Learning products and pipelines that will be deployed for our customers in order to prevent issues such as power outages, forced shutdowns, impact of climate change on the aging grid infrastructure and preventing wildfires.


• Researching, developing and deploying advanced algorithms for image and video processing as well as computer vision.

• Working with Geospatial visual data such as Satellite imagery and LiDAR to build data ingestion and processing pipelines

• Developing Machine Vision AI models for Semantic Segmentation, Anomaly Detection and Entity Classification for Satellite imagery and LiDAR data

• Build Machine Vision and Computer Vision models for fault and anomaly detection for RGB and Infrared imagery

• Experience training models on VMs, Google Kubernetes and Compute Engines

• Build Predictive models and Causal Inference models for generating predictive insights

• Deploy dynamic models on cloud infrastructure and as service APIs

• Integrating ML models with our Software Platform

• Implementing ML/AI solutions for web and mobile platforms through the collaboration with Software engineers.


• A strong background in machine learning engineering . 3-5 years industry experience is ideal.

• MS/PhD in Machine Learning, Computer Science, Mathematics or related field with specialization in Machine Learning and/or Computer Graphics.

• Experience in image/video processing, computer vision, machine learning

• Strong experience working with RGB and Infrared imagery, Satellite imagery and LiDAR datasets

• Strong Experience working with CNNs, PyTorch, Fast RCNNs, Mask RCNNs, YOLO, ImageNets, Predictive models, Keras, Tensorflow

• Experience with Git, Docker, Compute Engine, VMs, Kubernetes Engine

• Experience deploying ML models in production

• Strong data science and machine learning skills

• Experience with Cloud Infrastructure such as Google Cloud Platform, AWS

• Experience with deploying Machine Learning models in production on Google Cloud Platform, AWS

• Proficient in Python, PyTorch, PySpark, OpenCV, MLFlow, KubeFlow, Docker

• Strong analytical and problem-solving skills

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