Computer Vision Engineer - Flexible Growth Path

AgileEngine, LLC.; Richmond (VA); Hybrid; USD 65,000 - 95,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine, LLC in the United States is seeking a Junior/Middle Computer Vision Engineer to support data preparation, model training, and evaluation for an AI team handling large-scale image and video datasets.

You will curate labeling workflows, run training and evaluation jobs, document results, and collaborate with senior engineers on failure-case analysis. This is an early-career role with mentorship and growth toward applied modeling or MLOps.

Qualifications

• Authorized to work in the US without sponsorship.
• 1–3 years of experience in software engineering, data science, ML, or related field.
• Degree in CS/DS/Engineering/Math or equivalent practical experience.
• US-based engineers must reside in Dallas, TX and be onsite.
• Foundational coding in Python.
• Foundational ML concepts and workflows.
• Basic knowledge of computer vision principles.
• Familiar with cloud environments and compute resources.
• Willing to learn in a mentorship-driven environment.
• Strong attention to data quality and documentation.

Responsibilities

• Curate large-scale image and video datasets and manage labeling workflows.
• Run model training and evaluation jobs, ensuring experiments run smoothly.
• Document training results and track model performance over time.
• Collaborate with senior engineers to analyze failure cases and drive improvements.
• Support AI/ML lifecycle tasks to speed production deployments.

Skills

Python

Data science

Machine learning

Computer vision

Cloud computing

Documentation

Education

Bachelors in CS/DS/Engineering/Math or related

Job description

AgileEngine, LLC in the United States is seeking a Junior/Middle Computer Vision Engineer to support data preparation, model training, and evaluation for an AI team handling large-scale image and video datasets.

You will curate labeling workflows, run training and evaluation jobs, document results, and collaborate with senior engineers on failure-case analysis. This is an early-career role with mentorship and growth toward applied modeling or MLOps.