Computer Vision Engineer
Role details
Job location
Tech stack
Job description
warehouse and parcel automation systems OCR and Vision AI solutions Realtime operational dashboards AI assistants for logistics operations integrations with enterprise logistics systems mobile scanning and warehouse applications intelligent workflow orchestration systems
We move fast, ship real products, and solve difficult operational problems.
What We Care About
We care more about:
what you've built how you think how fast you can execute your ability to solve problems
…than traditional resumes or degrees.
Show us:
products systems prototypes GitHub projects AI workflows demos side projects
Ideal Candidate
You are:
highly technical product-minded AI-native fast-moving self-driven obsessed with building great user experiences comfortable with ambiguity excited about AI transforming real industries
Please include:
Please send:
LinkedIn profile GitHub portfolio/projects examples of AI systems you've built anything you're proud of building
Are you
An engineer who enjoys solving complex visual AI problems and turning emerging AI technologies into practical, reliable solutions.
Comfortable experimenting with new models and techniques while maintaining the engineering discipline required to deploy scalable, production-ready AI systems.
Passionate about computer vision, multimodal AI, and building intelligent systems that understand the visual world, we would like to hear from you., A talented and motivated AI Vision Engineer will design, develop, and deploy advanced computer vision and visual AI solutions. This role will focus on building intelligent systems capable of understanding and analyzing images and video using modern computer vision, deep learning, and multimodal AI technologies., The ideal candidate combines strong software engineering skills with hands-on experience developing machine learning and computer vision models. You will work on real-world AI applications and help move solutions from research and experimentation into scalable production environments., * Design, develop, and optimize computer vision and visual AI solutions for image and video analysis.
- Build and train deep learning models for object detection, image classification, segmentation, tracking, OCR, anomaly detection, and other vision applications.
- Develop image and video processing pipelines using Python, OpenCV, and modern AI frameworks.
- Fine-tune and evaluate CNN, transformer-based, and vision-language models for domain-specific applications.
- Collect, prepare, analyze, and manage image and video datasets used for model development.
- Develop data augmentation and preprocessing strategies to improve model performance and robustness.
- Evaluate models using appropriate metrics, including precision, recall, F1 score, IoU, mAP, latency, and inference performance.
- Conduct detailed failure analysis and identify opportunities to improve model accuracy and reliability.
- Optimize AI models for real-time and production inference using technologies such as ONNX, TensorRT, CUDA, and model quantization.
- Deploy computer vision models to cloud, edge, GPU, and production environments.
- Build APIs and services that integrate AI vision capabilities into enterprise applications and workflows.
- Implement model monitoring, experiment tracking, dataset versioning, and reproducible machine learning pipelines.
- Collaborate with software engineers, data engineers, product teams, and business stakeholders to translate requirements into practical AI solutions.
- Research and evaluate emerging computer vision, multimodal AI, and vision-language technologies.
Requirements
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical field, or equivalent practical experience.
- Strong programming skills in Python.
- Experience with computer vision and image processing techniques.
- Hands-on experience with PyTorch, TensorFlow, or similar deep learning frameworks.
- Experience developing deep learning models using CNNs, transformers, or related architectures.
- Knowledge of object detection, image classification, segmentation, or video analysis.
- Strong understanding of machine learning fundamentals, including training, validation, optimization, and model evaluation.
- Experience working with image and video datasets, annotation workflows, and data augmentation.
- Familiarity with Git, Linux, Docker, and modern software development practices.
- Strong analytical and problem-solving skills.
Preferred Qualifications
- Experience with OpenCV and modern computer vision libraries.
- Experience with object detection frameworks and architectures such as YOLO, Faster R-CNN, or similar technologies.
- Experience with vision-language models, multimodal AI, visual embeddings, or visual search.
- Experience optimizing models using ONNX, TensorRT, CUDA, quantization, or GPU acceleration.
- Experience deploying AI models to cloud or edge computing environments.
- Proficiency in C++ for high-performance or real-time vision applications.
- Experience with MLOps tools for experiment tracking, model versioning, dataset versioning, and production monitoring.
- Knowledge of camera calibration, 3D vision, stereo vision, depth estimation, or geometric computer vision.
- Experience developing real-time image or video processing systems.
Technical Skills
Programming: Python, C++ Computer Vision: OpenCV, image processing, video analytics, object detection, segmentation, tracking, OCR AI & Deep Learning: PyTorch, TensorFlow, CNNs, transformers, vision-language models Model Deployment: ONNX, TensorRT, CUDA, model quantization Infrastructure: Docker, Linux, Git, cloud and edge deployment MLOps: Experiment tracking, model versioning, dataset management, model monitoring
Benefits & conditions
Pulled from the full job description 401(k) Health insurance Paid time off Vision insurance Dental insurance Life insurance, * 401(k)
- Dental insurance
- Health insurance
- Life insurance
- Paid time off
- Vision insurance