Senior Computer Vision & Machine Learning Engineer New Remote, US

Buzz Solutions, Inc.; Northern (KY); Hybrid; USD 150,000 - 210,000; Full time

Job summary

Buzz Solutions, Inc. seeks a Senior Computer Vision & Machine Learning Engineer to advance our CV initiatives for power grid analysis through production-ready models.

You’ll bridge cutting-edge research and production systems, reading papers, adapting novel methods, and turning them into deployed solutions with autonomy. You will own end-to-end projects—from framing to monitoring—collaborating with ML engineers to deliver robust, scalable solutions that meet latency and reliability goals in a

Qualifications

• 5-10 years of industry experience in computer vision and machine learning.
• Image classification, vision transformers, and foundation models.
• Proven track record deploying ML models in production.
• Ability to read ML research papers, extract key ideas, and implement them.
• Proficiency in Python and the core ML stack (PyTorch, OpenCV, NumPy, pandas).

Responsibilities

• Own end-to-end computer vision projects from problem framing through deployment.
• Translate client requirements and raw data into working CV solutions.
• Collaborate with engineers to deliver against milestones and client goals.
• Stay current with ML/CV research and evaluate applicability to our domain.
• Design experiments with systematic hyperparameter tuning and baselines.

Skills

Python

PyTorch

Vision transformers

Foundation models

Multi-modal computer vision

OpenCV

NumPy

Pandas

Scikit-Learn

Git

Docker

Lightning

CUDA

FastAPI

Pydantic

GitHub Actions

Experiment tracking

Tools

Lightning

CUDA

GitHub Actions

Job description

Senior 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. You'll operate with a high degree of autonomy.

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

• 5-10 years of industry experience in computer vision and machine learning.
• Image classification
• Vision transformers and foundation models
• Similarity search
• Proventrack recordof deploying andmaintainingML 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.
• Proficiencyin 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.
• Multi-modalcomputervision
• ExtractingmeasurementsfromGISand/ordronemetadataenrichedimagery

Additional information:

• This position does not include sponsorship for United States work authorization.