Note: The job is a remote job and is open to candidates in USA. Buzz Solutions develops AI-powered analytics and maintenance solutions for power grid infrastructure, using computer vision to improve safety, reliability, and operational efficiency. The Senior Computer Vision & Machine Learning Engineer will lead end-to-end computer vision projects, adapt research into production-ready models, build ML pipelines and serving systems, and communicate technical findings to stakeholders and clients.
Responsibilities
- Own and deliver end-to-end computer vision projects focused on:
- Equipment defect detection
- Thermal anomaly identification
- Vegetation encroachment monitoring
- Surveillance of closed areas for human and animal intrusion
- Scope, plan, and execute your own projects from problem framing through production deployment and monitoring
- Deliver on client projects, translating client requirements and raw data into working computer vision solutions
- Contribute to shared team projects, coordinating with other engineers to deliver against common milestones
- Stay current with ML/CV research, identify promising methods, and evaluate their applicability to our domain
- Adapt and implement algorithms from papers, validating against baselines and benchmarking for production viability
- Bring the latest advances in deep learning and generative AI to bear on model training, accuracy, and reliability
- Design and execute experiments with systematic hyperparameter tuning, ablation studies, and appropriate baselines
- Perform structured error analysis: categorize failure modes (false positives, missed detections, localization errors, misclassifications) and break down performance by data slices (object size, occlusion, image quality)
- Select and justify model architectures based on task requirements, latency, and accuracy tradeoffs
- Develop production-grade Python libraries for the complete ML lifecycle
- Design and implement data pipelines including ingestion, preprocessing, annotation workflows, and quality monitoring
- Own experiment tracking and model versioning: configurations, random seeds, dataset versions, environment specs, and model checkpoints
- Build model serving pipelines that meet latency and throughput requirements
- Conduct thorough code reviews and write integration tests for ML pipelines
- Share knowledge with teammates and contribute to best practices for model development, evaluation, deployment, and monitoring
- Advocate for and uphold software quality standards within the ML team
- Communicate research findings, technical decisions, and model limitations clearly to stakeholders and clients
Skills
- 5–10 years of industry experience in computer vision and machine learning
- Deep expertise in modern computer vision and deep neural networks, including:
- Object detection
- Semantic segmentation
- Image classification
- Vision transformers and foundation models
- Vision language models
- Similarity search
- Proven track record of deploying and maintaining ML models in production
- Experience selecting, fine-tuning, and adapting model architectures (CNNs, transformers, foundation models) for specific use cases
- Demonstrated ability to read ML research papers, extract the key ideas, and implement them
- Ability to debug training instabilities and conduct systematic error analysis
- Proficiency in Python and the core ML stack:
- PyTorch and Lightning
- OpenCV
- NumPy and pandas
- Scikit-Learn
- FastAPI and Pydantic
- Strong software engineering practices, including:
- Git version control
- Unit and integration testing (Pytest)
- CI/CD pipelines (GitHub Actions)
- Docker and reproducible environments
- Experiment tracking and model versioning
- ML DevOps
- Python type hinting
- Proven ability to own technical projects independently, from problem framing through production deployment
- This position does not include sponsorship for United States work authorization
- Multi-modal computer vision
- Custom object detection model development
- Generative models for data augmentation
- ML deployment on edge devices
- Extracting measurements from GIS and/or drone metadata enriched imagery
- Model quantization
- Systematic hyperparameter tuning
Benefits
- Support to keep growing
- High degree of autonomy
Company Overview