Machine Learning Engineer
Palo Alto, CA, USA
Type of Job
About the job
The role will be responsible for researching,
developing and deploying advanced algorithms for image and video processing
as well as computer vision; building Machine Vision and Computer Vision
models for fault and anomaly detection; experience training models on Google
Kubernetes and Compute Engines; building Predictive models and Causal
Inference models for generating predictive insights; deploying 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.
Master’s degree in Computer Science or a closely
related field of concentration and 1 year of experience in job offered or related
Education or Experience to include:
- image/video processing, computer vision, machine learning;
- working with CNNs, RNNs, Neural Networks, Predictive models, Keras,
Tensorflow, Git, Docker, Compute Engine, VMs, Kubernetes Engine;
- deploying Machine Learning models in production on Google Cloud Platform,
- proficiency in Python, PySpark, OpenCV, MLFlow, KubeFlow, Docker.
Employer will accept any suitable combination of education, training and
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.
Palo Alto, CA, USA