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AI Computer Vision Consultant

AI Computer Vision Consultant

Artificial Intelligence Global CompanyIndia
4 days ago
Job description

AIGC is looking for an experienced AI Computer Vision Consultant to join our innovative team in Bangalore. If you’re passionate about AI, Machine Learning, and real-world Computer Vision applications, this is your chance to make an impact in the Energy, Oil & Gas, Petrochemicals, Utilities, and Manufacturing sectors.

Location : Bangalore – Manyata Tech Park

Experience : 12+ years overall (8+ in AI / ML & Computer Vision)

Minimum 12 years of overall industry experience with at least 8 years in AI / ML and Computer Vision.

  • At least 3 full-lifecycle implementations of computer vision projects (from requirement gathering to production deployment).
  • Proven experience in industrial CV applications (e.g., quality inspection, process monitoring) and CCTV-based use cases (e.g., surveillance, anomaly detection).
  • Hands-on deployment of computer vision solutions on edge servers (e.g., NVIDIA Jetson, Intel NUC).

Demonstrated experience in technical consulting, RFP responses, proposal writing, and client management.

  • Prior experience in managing and delivering AI / ML projects, including team and timeline management.
  • Experience in the delivery of end-to-end analytical solutions (analyze, design, implement, test, and deploy) and implementation of AI and Advanced Analytics projects for Energy, Oil & Gas, Refining, Petrochemicals, Chemicals, Mining, Supply Chain, Utilities, Power, and Manufacturing industries.
  • Experience in leading a team and training young data scientists.
  • Good understanding of the AI ecosystem and capabilities
  • Exposure to data transformation and data structuring as part of model building
  • Building simple yet best-fit solution design or logic design for complex data challenges or industry use cases.
  • Hands-on experience with DevOps & ML Operation tools including version control tools such as GIT.
  • Understanding of information systems security and network architecture
  • Excellent analytical and problem-solving skills
  • Ability to face and interact with clients and deliver technical solutions demonstrations and presentations.
  • Experience in industrial computer vision applications using AI for tasks such as object detection and tracking.
  • Experience working with GIS aerial drone-based and satellite-based data analytics and modeling for anomaly detection is nice to have.
  • Experience in Computer Vision applications for corrosion monitoring of industrial assets and pipes is a plus.
  • Experience in the latest computer vision frameworks for pre-trained models and transfer learning.
  • Experience in industrial automation use cases using computer vision AI.
  • Certification in AI / Data Analytics / Deep Learning is desired.
  • Experience in real-time (e.g., video, CCTV camera streams) video analytics pipeline.
  • Process or Power industry experience is desired.
  • Experience in cloud deployment platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) is nice to have.
  • Good in documentation practices, writing reports, and project protocols.
  • High level of technical aptitude
  • Microsoft Office and technical presentation skills.
  • Technical Skills & Competencies : Computer Vision Tools & Libraries :

  • OpenCV, TensorFlow, PyTorch, YOLO
  • Image and video processing, object detection, segmentation, pose estimation
  • Real-time CV systems, CCTV integration, RTSP stream processing
  • Coding different object detection neural network architectures such as CNN, R-CNN, Fast R-CNN, Faster R-CNN, SSD, and YOLO. Programming & Frameworks :

  • Strong in Python; knowledge of C++ is a plus
  • Familiarity with Edge AI frameworks (NVIDIA DeepStream, TensorRT, OpenVINO) Deployment & Architecture :
  • Edge computing architectures, Docker, Kubernetes, REST APIs
  • Cloud & on-premise hybrid deployment strategies (Azure, AWS, GCP) Other AI Skills (Nice to Have) :
  • Predictive Analytics, Time-Series Forecasting
  • Generative AI (e.g., LLMs, image generation models)
  • Agentic AI and AI pipeline orchestration
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