Remote Senior Computer Vision & ML Engineer - Power Grid AI

Buzz Solutions, Inc.; United States; 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

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