[Hiring] Computer Vision & Machine Learning Engineer @Buzz Solutions

Role Description

We're looking for a Machine Learning Engineer to join our computer vision team and help build our foundational model capabilities. You'll bridge the gap between cutting-edge research and production systems, reading papers, adapting novel algorithms, and turning them into reliable, deployed models for power grid analysis. 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

• 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
• Own and deliver end-to-end computer vision projects focused on:
  • Equipment defect detection
  • Thermal anomaly identification
  • Vegetation encroachment monitoring
• 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
• Design and implement data pipelines including ingestion, preprocessing, annotation workflows, and quality monitoring
• 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
• Communicate research findings, technical decisions, and model limitations clearly to stakeholders

Qualifications

• 2-4 years of industry experience in computer vision and machine learning
• Solid understanding of modern computer vision and deep neural networks including:
  • Object detection
  • Semantic segmentation
  • Image classification
  • Vision transformers and foundation models
• Demonstrated ability to read ML research papers, extract key ideas, and implement them
• Experience adapting published methods to specific use cases and validating against baselines
• Experience selecting, fine-tuning, and adapting model architectures (CNNs, transformers, foundation models) for specific use cases
• Ability to debug training instabilities and conduct systematic error analysis
• Proficiency in Python and core ML libraries:
  • PyTorch and Lightning
  • OpenCV
  • NumPy and pandas
  • Scikit-Learn
• Strong software engineering practices:
  • Git version control
  • Unit and integration testing (Pytest)
  • CI/CD pipelines (GitHub Actions)
  • Experiment tracking and model versioning
  • Docker and reproducible environments
  • Python type hinting

Requirements

• * Buzz Solutions does not provide Visa sponsorship for work authorizations in the United States at this time *