About Us
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.
Job Description
We're looking for an entry/mid-level Applied Machine Learning Platform Engineer to join our computer vision team and help improve the databases, cloud infrastructure, and tooling our team builds on. You'll build tooling and infrastructure to help scale our training and data pipelines. You'll work within a team of experienced ML engineers with the autonomy to drive your own projects and the support to keep growing.
Responsibilities
- Design, build, and maintain scalable training infrastructure for computer vision workloads
- Implement and manage distributed training pipelines (multi-GPU, multi-node) to support large-scale model training and hyperparameter tuning
- Build and maintain robust data pipelines for ML development
- Design database schemas and storage strategies for managing large training datasets, annotations, and model artifacts
- Implement and manage feature stores, data versioning, and experiment tracking to support reliable model iteration
- Automate existing analysis workflows
- Maintain clear documentation for platform components, data contracts, and deployment processes
- Communicate infrastructure decisions, tradeoffs, and system limitations clearly to ML engineers and stakeholders
- Conduct thorough code reviews and write integration tests for ML pipelines
Qualifications & Experience
- 2-4 years of industry experience in platform, backend, data, or MLOps engineering roles
- Python proficiency — idiomatic code, type hints, async patterns, packaging, and performance-aware implementation
- Strong software engineering fundamentals — testing, code review, API design, component-level system design
- Hands-on experience building and operating distributed cloud machine learning infrastructure
- Designing and maintaining scalable training infrastructure, managing ML platform reliability, optimizing data pipelines for throughput at scale
- Experience with database design and data systems for ML workloads — schema design, query optimization, and storage strategies for large-scale datasets
- Excels at workflow orchestration and automation
- Solid proficiency in Python and core ML tooling:
- Python ecosystem: Pytest, UV, FastAPI, Pydantic
- Tooling: Git, Docker, UV
- Tracking: MLflow, Weights & Biases, or equivalent
- Automation: Github Actions, CI/CD, Prefect or equivalent
- Infrastructure: AWS, GCP, Kubernetes, Helm, Terraform or equivalent
- Databases: postgres, DynamoDB, Bigtable
* Buzz Solutions does not provide Visa sponsorship for work authorizations in the United States at this time *
Skills Required
- 2-4 years of industry experience in platform, backend, data, or MLOps engineering roles
- Python proficiency including idiomatic code and performance-aware implementation
- Strong software engineering fundamentals including testing and API design
- Experience with distributed cloud machine learning infrastructure
- Database design and data systems for ML workloads
- Workflow orchestration and automation
What We Do
Buzz Solutions provides AI powered Software Platform and Predictive Analytics for detecting faults and anomalies on power line assets and components for power utilities. We automate the process of inspection of power lines for faults and anomalies by analyzing millions of visual data points captured by helicopters, drones and linemen in the field for power companies thus saving them great amount of time, money as well as preventing wildfires, power outages and other climate change effects on the physical grid infrastructure.
