Computer Vision Engineer (Junior/Mid) | Remote & Office Flex

AgileEngine; Houston (TX); On-site; 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 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, and collaborate with senior engineers on failure-case analysis, with a clear growth path into applied modeling or MLOps for an early-career engineer.

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 a related discipline (or equivalent practical experience).
• Foundational coding skills in Python.

Responsibilities

• Curate large-scale image and video datasets, manage labeling processes and workflows, and ensure the highest standards for dataset quality.
• Run model training and evaluation jobs, ensuring experiments are executed smoothly and efficiently.
• Document training results, maintain ongoing evaluation benchmarks, and track model performance over time.
• Collaborate with senior engineers to analyze model failure cases and identify areas for data or algorithmic improvement.
• Take ownership of foundational tasks that support the broader team’s AI/ML lifecycle, directly contributing to the speed and success of production deployments.

Skills

Python

Machine learning

Data science

Software engineering

English (upper-intermediate)

Education

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics

Tools

Cloud platforms

Job description

AgileEngine 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 annotation workflows, run training and evaluation jobs, and collaborate with senior engineers on failure-case analysis, with a clear growth path into applied modeling or MLOps for an early-career engineer.