• Job Description

  Req#: 26-00290
  Computer Vision Researcher
  
  Job Title
  
  Computer Vision Researcher
  
  Job Summary
  
  We are seeking a highly skilled Computer Vision Researcher to develop cutting-edge computer vision and deep learning solutions for real-world applications. The ideal candidate will have strong expertise in image processing, deep learning, vision transformers, object detection, image segmentation, and generative vision models. You will conduct research, build state-of-the-art models, and collaborate with engineering teams to deploy scalable computer vision solutions.
  
  Key Responsibilities
  
  • Conduct research and develop advanced computer vision algorithms for image and video understanding.
  • Design, implement, and optimize deep learning models for tasks such as image classification, object detection, semantic and instance segmentation, pose estimation, optical character recognition (OCR), tracking, and video analytics.
  • Develop and fine-tune vision foundation models, vision transformers (ViTs), and multimodal vision-language models for domain-specific applications.
  • Build scalable training, evaluation, and inference pipelines for computer vision systems.
  • Work with large-scale image and video datasets, including data collection, annotation, augmentation, and quality assessment.
  • Evaluate model performance using industry-standard benchmarks and metrics, and optimize models for accuracy, latency, and efficiency.
  • Collaborate with machine learning engineers, data scientists, software engineers, and product teams to transition research into production.
  • Stay up to date with the latest advancements in computer vision, deep learning, and generative AI by reviewing research publications and implementing relevant techniques.
  
  Required Qualifications
  
  • Master's or Ph.D. in Computer Science, Artificial Intelligence, Computer Vision, Machine Learning, Electrical Engineering, or a related field.
  • 3+ years of experience in computer vision research or applied machine learning.
  • Strong understanding of:
    
    • Image Processing
    • Deep Learning
    • Convolutional Neural Networks (CNNs)
    • Vision Transformers (ViTs)
    • Object Detection
    • Image Segmentation
    • Feature Extraction
    • Representation Learning
    • Self-Supervised Learning
  • Proficiency in Python.
  • Hands-on experience with PyTorch or TensorFlow.
  • Experience with computer vision libraries such as OpenCV, Detectron2, MMDetection, Ultralytics YOLO, or OpenMMLab.
  • Strong understanding of model evaluation metrics, including mAP, IoU, precision, recall, and F1-score.
  • Experience with GPU acceleration, distributed training, and model optimization.
  • Familiarity with Git, Docker, Linux, and cloud platforms (AWS, Azure, or Google Cloud).
  
  Preferred Qualifications
  
  • Experience with vision foundation models such as Segment Anything Model (SAM), DINOv2, CLIP, Florence, or Grounding DINO.
  • Experience with OCR, document AI, medical imaging, satellite imagery, autonomous driving, robotics, or industrial inspection.
  • Knowledge of 3D computer vision, depth estimation, point cloud processing, SLAM, or neural rendering.
  • Experience with generative AI models for image synthesis and editing.
  • Publications in leading AI conferences such as CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML, or WACV.
  • Contributions to open-source computer vision projects.
  
  Technical Skills
  
  • Python
  • PyTorch / TensorFlow
  • OpenCV
  • Detectron2
  • MMDetection
  • Ultralytics YOLO
  • Hugging Face Transformers
  • CUDA
  • DeepSpeed
  • NumPy
  • Pandas
  • Git
  • Docker
  • Kubernetes (preferred)
  • Linux
  • SQL
  • AWS / Azure / Google Cloud
  
  Soft Skills
  
  • Strong analytical and research skills.
  • Excellent problem-solving and debugging abilities.
  • Effective communication and technical documentation skills.
  • Ability to collaborate with cross-functional teams.
  • Curiosity, innovation, and a passion for advancing computer vision research.
  
  Nice to Have
  
  • Experience with multimodal AI and vision-language models.
  • Familiarity with large language models (LLMs) and retrieval-augmented generation (RAG).
  • Experience with MLOps, model deployment, and CI/CD pipelines.
  • Knowledge of reinforcement learning for vision-based decision-making.
  • Experience with synthetic data generation and simulation environments.
  
  Benefits
  
  • Competitive salary and performance-based incentives.
  • Flexible work arrangements.
  • Comprehensive health and wellness benefits.
  • Learning, certification, and conference sponsorship opportunities.
  • Access to high-performance GPU infrastructure.
  • Opportunity to work on cutting-edge computer vision research and production AI systems.

• About the company

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