Junior/Middle Computer Vision Engineer

About the role

We are looking for a Junior/Middle Computer Vision Engineer to support high-volume execution across data preparation, model training, and evaluation for an AI team working with large-scale image and video datasets. You will curate and manage annotation workflows, run model training and evaluation jobs, maintain benchmarks, and collaborate with senior engineers on failure-case analysis. The role offers a a clear growth path into applied modeling or MLOps for an early-career engineer eager to build hands-on AI experience.

What you will do

• 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.

Must haves

• 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);
• Engineers located in the US must reside in Dallas, TX, and be open to working from the office (onsite);
• Foundational coding skills in Python;
• Foundational understanding of machine learning concepts and workflows;
• Basic knowledge of computer vision principles (e.g., image processing, object detection basics);
• Basic familiarity with cloud environments and compute resources;
• A strong, demonstrable willingness to learn and adapt in a fast-paced, mentorship-driven environment;
• Excellent attention to detail, specifically regarding data quality and documentation;
• Upper-intermediate English level.