Computer Vision Engineer (Junior–Mid) — Flexible/Hybrid Growth

AgileEngine, LLC.; Tallahassee (FL); Hybrid; USD 60,000 - 90,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine is seeking a Junior/Middle Computer Vision Engineer to support high-volume data preparation, model training, and evaluation for an AI team handling large-scale image and video datasets. You will curate annotation workflows, run training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis.

The role offers a clear growth path into applied modeling or MLOps for an early-career engineer eager to build hands-on AI experience.

Qualifications

• 1 to 3 years of experience in software engineering, data science, machine learning, or a related field.
• Degree in Computer Science, Data Science, Engineering, Mathematics, or related discipline (or equivalent practical experience).
• Foundational Python coding skills.
• Foundational understanding of machine learning concepts and workflows.
• Basic knowledge of computer vision principles and imaging.

Responsibilities

• Curate large-scale image and video datasets and manage labeling workflows to ensure dataset quality.
• Run model training and evaluation jobs, ensuring experiments execute smoothly and efficiently.
• Document training results and maintain ongoing evaluation benchmarks.
• Collaborate with senior engineers on failure-case analysis and data/algorithm improvements.
• Support foundational tasks across the AI/ML lifecycle to aid production deployments.

Skills

Python

Machine learning concepts

Data science basics

Computer vision basics

Education

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or related discipline

Job description

AgileEngine is seeking a Junior/Middle Computer Vision Engineer to support high-volume data preparation, model training, and evaluation for an AI team handling large-scale image and video datasets. You will curate annotation workflows, run training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis.

The role offers a clear growth path into applied modeling or MLOps for an early-career engineer eager to build hands-on AI experience.