Computer Vision - Data Scientist
Nextgen Invent Corporation
The role
Job description
Experience: 2+ Years
Job Location: WFH/Remote
No. of Positions: Multiple
Qualification: Ph.D. in Computer Science, Artificial Intelligence, Computer Vision, Machine Learning, Data Science, Applied Mathematics, or a related field
Work Timings: 1:30 PM IST – 10:30 PM IST
NextGen Invent is seeking a Computer Vision - Data Scientist to join its Data Science Practice. This role will focus on designing, developing, and deploying enterprise-scale Computer Vision solutions that solve complex business challenges using cutting-edge AI and Deep Learning technologies.
Key Responsibilities
- Design, develop, and deploy Computer Vision solutions for enterprise use cases.
- Build and optimize models for image classification, object detection, segmentation, OCR, tracking, and video analytics.
- Develop end-to-end AI pipelines covering data preparation, model training, evaluation, deployment, and monitoring.
- Apply state-of-the-art Deep Learning architectures, including CNNs, Vision Transformers (ViTs), and multimodal AI models.
- Deploy scalable Computer Vision applications across cloud and edge environments.
- Analyze large-scale image, video, and multimodal datasets to generate actionable insights.
- Benchmark, evaluate, and optimize model performance using industry-standard metrics.
- Maintain and enhance existing AI solutions to improve accuracy, efficiency, and scalability.
- Collaborate with engineering, product, and business teams to translate requirements into AI-driven solutions.
- Implement MLOps best practices for model lifecycle management, monitoring, and continuous improvement.
- Stay current with emerging research and advancements in Computer Vision and AI, driving innovation within the organization.
Skills, Knowledge & Experience
- Must have a Ph.D. in an analytical or technical field (e.g., Artificial Intelligence, Computer Vision, Machine Learning, Data Science, Applied Mathematics)
- Minimum 2+ years of hands-on experience building and deploying Computer Vision solutions in production environments.
- Strong understanding of Computer Vision, Deep Learning, Machine Learning, and Image Processing techniques.
- Experience with object detection, image classification, segmentation, OCR, pose estimation, and video analytics.
- Hands-on experience with PyTorch, TensorFlow, Keras, OpenCV, or similar frameworks.
- Strong knowledge of modern Computer Vision architectures such as YOLO, Faster R-CNN, Mask R-CNN, ResNet, EfficientNet, DETR, and Vision Transformers.
- Proficiency in Python and SQL is a must.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Familiarity with Docker, Kubernetes, CI/CD pipelines, and MLOps tools.
- Experience with model evaluation, optimization, and deployment of scalable AI systems.
- Strong analytical, problem-solving, and communication skills.
- Ability to collaborate effectively with cross-functional teams and stakeholders.
Preferred
- Experience with vision-language models and multimodal AI frameworks such as CLIP and BLIP.
- Experience deploying real-time or edge AI applications.
- Familiarity with annotation tools such as CVAT, Labelbox, or Supervisely.
- Domain experience in Healthcare, Manufacturing, Retail, Automotive,
- Experience working with US or European clients.
- Leadership or mentoring experience in AI/ML projects.
This job description is not intended to cover or contain a comprehensive listing of all responsibilities, duties, or activities required for the role. Responsibilities may change, or new responsibilities may be assigned, at any time with or without notice.
If you are a motivated professional with a passion for delivering impactful solutions, we'd love to hear from you. Apply today to be part of a dynamic and forward-thinking team at NextGen Invent.
Originally posted on Himalayas
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Listing details
- Listed location
- United States
- Employment
- Full Time
- Published
- Jul 19, 2026
Listing trust
- Observed through
- Himalayas
- Listing last observed
- Jul 26, 2026
Work-from eligibility is based on normalized evidence in the listing: United States.
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