Computer Vision & Machine Learning Engineer New Remote, US

Buzz Solutions, Inc.; Northern (KY); Hybrid; USD 130,000 - 180,000; Full time

Job summary

Buzz Solutions, Inc. seeks a Computer Vision & Machine Learning Engineer to advance CV initiatives for power grid analytics. This remote US role offers autonomy to own projects from problem framing to production.

You will build and deploy models, work with transformers and foundation models, and collaborate with ML engineers to deliver reliable solutions for clients and internal products.

Qualifications

• 2-5 years of industry experience in computer vision and ML.
• Experience with image classification and foundation models.
• Proficiency in Python and the core ML stack (PyTorch, OpenCV, NumPy).
• Ability to read ML research papers and implement ideas.
• Experience taking an ML model into production.

Responsibilities

• Own and deliver end-to-end computer vision projects from problem framing to deployment.
• Translate client requirements and data into working CV solutions.
• Collaborate with engineers to meet milestones and production goals.
• Develop production-grade ML tooling and data pipelines.
• Conduct experiments, evaluate baselines, and monitor models in production.

Skills

Computer vision

Machine learning

Vision transformers

Foundation models

Similarity search

Production ML

Python

PyTorch

OpenCV

NumPy

Pandas

Scikit-Learn

FastAPI

Git

CI/CD

Docker

Testing

Experiment tracking

Tools

PyTorch

OpenCV

NumPy

Pandas

Scikit-Learn

FastAPI

Pydantic

Git

GitHub Actions

Docker

pytest

Job description

Computer Vision & Machine Learning Engineer

Remote, US

Job Description

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.

We're looking for a Machine Learning Engineer to advance our computer vision initiatives 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

• 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.

Research and experimentation

• Stay current with ML/CV research,identifypromising methods, and evaluate their applicability to our domain.
• Adapt and implement algorithms from papers,validatingagainst 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, andappropriate 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 accuracytradeoffs.

Engineering and production

• 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.

Collaboration and craft

• 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.

Qualifications & Experience

• 2-5 years of industry experience in computer vision and machine learning.
• Image classification
• Vision transformers and foundation models
• Similarity search
• Experience taking at least one ML model into productionandmaintainingit there.
• 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.
• Proficiencyin Python and the core ML stack:
  • PyTorchand 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.

Desired Additional Experience

• Extracting measurements from GIS and/or drone-metadata-enriched imagery
• Model quantization and latency optimization for edge deployment
• Systematic hyperparameter tuning at scale
• Energy, utilities, geospatial, or industrial inspection domains

Additional information:

• This position does not include sponsorship forUnited States work authorization.