Backend Engineer: MLOps and DevOps

Job Location

San Francisco Bay Area, CA, USA

Type of Job

Full Time

Job Level


About the job

Job Responsibilities:

  • 2-3+ years of industry experience maintaining backend infrastructure, deploying models/algorithms as REST APIs, deploying products on production environments

  • Deploy our ML/AI models as REST APIs and integrating them as secure pipelines with client’s cloud infrastructure systems

  • Monitoring and Maintaining these deployed pipelines

  • Maintaining our cloud infrastructure and end-to-end pipelines for our ML/AI products as well as our software platform

To apply, send your resume (cover letter optional) to


  • Master’s or PhD in Computer Science, Engineering or a quantitative degree

  • Industry experience with Git, Docker, Compute Engine, Virtual Machines, Kubernetes Engine, Kubeflow, MLFlow, REST APIs, Load Balancers, Building end-to-end pipelines on cloud infrastructures, cloud infrastructure management, GCP Cloud Run

  • Experience with deploying Machine Learning models in production as REST APIs or Batch Processes on Google Cloud Platform, AWS and Azure

  • Proficient and industry experience with Python, PyTorch, SQL, Tensorflow, Keras, Kubeflow, Docker, FastAPI, Flask, Javascript, Node.js, Postman for API testing, MongoDB, GCP datastore and Firestore

  • Industry experience with integrating backend pipelines and APIs with customer systems (cloud infrastructures)

  • Strong analytical and problem-solving skills

About us

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.


San Francisco Bay Area, CA, USA