OVA.Work
Posted 98 days agoVerified live 13h ago
Computer Vision Engineer
Brief overview
New York, NYHybrid
UndergradOr in progress
1+ yrsMinimum
Strong programming skills in PythonKnowledge of software engineering best practicesPythonC++ (preferred)SQLGitOpenCVPillowScikit-imageAlbumentationsPyTorchTensorFlowKerasCNNsResNetEfficientNetVision Transformer (ViT)
About the company
OVA.Workova.work
OVA is the most advanced Automated, Intelligent, intuitive On-boarding platform for Staffing Firms of all sizes.
Job description
Summary
OVA.Work is seeking a Computer Vision Engineer to design, develop, and deploy AI solutions that analyze images and videos. The role involves building scalable solutions for various applications including object detection and image classification.
Responsibilities
- Design and develop computer vision and deep learning models
- Build image and video processing pipelines
- Train, fine-tune, and evaluate computer vision models
- Develop applications for:
- Image classification
- Object detection
- Object tracking
- Image segmentation
- OCR (Optical Character Recognition)
- Face detection and recognition
- Pose estimation
- Video analytics
- Optimize models for speed, accuracy, and deployment
- Deploy models using APIs or edge devices
- Collaborate with data scientists, software engineers, and product teams
- Monitor model performance and improve production systems
Skills
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Electronics, Robotics, or a related field
- Strong programming skills in Python
- Solid understanding of machine learning and deep learning
- Experience working with image and video datasets
- Knowledge of software engineering best practices
- Python
- C++ (preferred)
- SQL
- Git
- OpenCV
- Pillow
- Scikit-image
- Albumentations
- PyTorch
- TensorFlow
- Keras
- CNNs
- ResNet
- EfficientNet
- Vision Transformer (ViT)
- YOLO
- Faster R-CNN
- Mask R-CNN
- U-Net
- SSD
- Image Classification
- Object Detection
- Image Segmentation
- Feature Extraction
- Transfer Learning
- Model Optimization
- Hyperparameter Tuning
- FastAPI or Flask
- Docker
- Kubernetes (preferred)
- ONNX
- TensorRT
- NVIDIA CUDA
- Edge AI deployment
- AWS
- Microsoft Azure
- Google Cloud Platform (GCP)
- Strong analytical and problem-solving abilities
- Good communication skills
- Team collaboration
- Attention to detail
- Ability to work in an Agile environment
- Experience with real-time video analytics
- Knowledge of OCR and document AI
- Experience with edge devices such as NVIDIA Jetson
- Familiarity with 3D vision, LiDAR, or depth cameras
- Understanding of MLOps and CI/CD pipelines
- Experience working with large-scale datasets such as COCO or ImageNet
- Vision-Language Models (VLMs)
- Multimodal AI
- Generative AI for images
- Image captioning
- Diffusion models
- Stable Diffusion
- Retrieval-Augmented Generation (RAG) with image embeddings
- LangChain or similar orchestration frameworks
- Vector databases (e.g., FAISS, Pinecone)
Qualifications
Must Haves
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Electronics, Robotics, or a related field
- Strong programming skills in Python
- Solid understanding of machine learning and deep learning
- Experience working with image and video datasets
- Knowledge of software engineering best practices
- Python
- C++ (preferred)
- SQL
- Git
- OpenCV
- Pillow
- scikit-image
- Albumentations
- PyTorch
- TensorFlow
- Keras
- CNNs
- ResNet
- EfficientNet
- Vision Transformer (ViT)
- YOLO
- Faster R-CNN
- Mask R-CNN
- U-Net
- SSD
- Image Classification
- Object Detection
- Image Segmentation
- Feature Extraction
- Transfer Learning
- Model Optimization
- Hyperparameter Tuning
- FastAPI or Flask
- Docker
- Kubernetes (preferred)
- ONNX
- TensorRT
- NVIDIA CUDA
- Edge AI deployment
- AWS
- Microsoft Azure
- Google Cloud Platform (GCP)
- Strong analytical and problem-solving abilities
- Good communication skills
- Team collaboration
- Attention to detail
- Ability to work in an Agile environment
Nice to Haves
- Experience with real-time video analytics
- Knowledge of OCR and document AI
- Experience with edge devices such as NVIDIA Jetson
- Familiarity with 3D vision, LiDAR, or depth cameras
- Understanding of MLOps and CI/CD pipelines
- Experience working with large-scale datasets such as COCO or ImageNet
- Vision-Language Models (VLMs)
- Multimodal AI
- Generative AI for images
- Image captioning
- Diffusion models
- Stable Diffusion
- Retrieval-Augmented Generation (RAG) with image embeddings
- LangChain or similar orchestration frameworks
- Vector databases (e.g., FAISS, Pinecone)
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