Job Title: Computer Vision Engineer
Location: Remote – Colombia
Type of Contract: Full-Time | Remote | Contractor
Salary Range: Market Rates
Language Requirements: English (Professional/Fluent)

We are seeking a skilled Computer Vision Engineer with strong experience in deep learning and image/video analysis to join our growing team. You will play a key role in designing, building, and deploying production-grade computer vision systems that power intelligent products and data-driven automation. Your work will directly impact how the organization extracts insights from visual data, improves operational efficiency, and delivers scalable AI solutions.

Key Responsibilities

Design, develop, and deploy end-to-end computer vision pipelines for image and video processing use cases.
Build and train deep learning models for object detection, classification, segmentation, and tracking.
Implement and optimize models using frameworks such as PyTorch or TensorFlow for performance and accuracy.
Develop data preprocessing, augmentation, and labeling workflows to support large-scale vision datasets.
Integrate computer vision models into production systems via APIs, microservices, or edge deployments.
Optimize inference performance for real-time or resource-constrained environments.
Collaborate with ML engineers, data scientists, and product teams to translate business requirements into scalable vision solutions.

Must-Have Qualifications

3+ years of experience in computer vision, machine learning, or applied AI engineering.
Strong proficiency in Python and computer vision libraries such as OpenCV, NumPy, and PIL.
Hands-on experience with deep learning frameworks (PyTorch, TensorFlow, or equivalent).
Solid understanding of CNN-based architectures and modern vision models.
Experience working with image and video datasets, including data preparation and evaluation.
Familiarity with deploying ML models into production environments.
Ability to work independently and communicate effectively in a remote, distributed team.

Preferred Qualifications

Experience with cloud platforms (AWS, Azure, or GCP) for model training and deployment.
Familiarity with MLOps practices, model monitoring, and performance optimization.
Experience with real-time or edge-based computer vision systems.
Background in industries such as manufacturing, healthcare, retail, or security.

Originally posted on Himalayas

Computer Vision Engineer at Nearshore Business Solutions