Junior/Middle Computer Vision Engineer ID72410

AgileEngine

$70K — $95K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 1-3 years of experience in software engineering, data science, machine learning, or related field.
  • Degree in Computer Science, Data Science, Engineering, Mathematics, or equivalent practical experience.
  • Foundational coding skills in Python.
  • Basic knowledge of machine learning concepts and workflows.
  • Basic knowledge of computer vision principles, including image processing and object detection basics.
  • Familiarity with cloud environments and compute resources.
  • Strong willingness to learn in a mentorship-driven environment.

Responsibilities

  • Curate and manage large-scale image and video datasets for high-quality standards.
  • Run smooth model training and evaluation jobs to ensure efficient experimentation.
  • Document training results and maintain evaluation benchmarks over time.
  • Collaborate on analyzing model failure cases for potential improvements.
  • Own foundational tasks that enhance the AI/ML lifecycle for production deployments.

Benefits

  • Professional growth opportunities through mentorship and personalized roadmaps.
  • Education, fitness, and team activity budgets as part of compensation.
  • Engagement in exciting projects with Fortune 500 and top product companies.
  • Flexibility in schedule with options for remote and onsite work.
Full Job Description
Job Description

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

- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;

- 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.

PERKS AND BENEFITS

- Professional growth: Mentorship, TechTalks, and personalized growth roadmaps.

- Competitive compensation: USD-based pay with education, fitness, and team activity budgets.

- Exciting projects: Modern solutions with Fortune 500 and top product companies.

- Flextime: Flexible schedule with remote and office options.

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