Computer Vision Engineer
1 month ago
Experience :
- 8 - 12 years of overall 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.
- Proposed, Designed, developed, deployed, and maintained at least a couple of data science models. (Real world projects).
- Experience in leading a team and training young data scientists.
- Good understanding of the AI ecosystem and capabilities
- 10+ years of work in building industrial computer vision applications using AI.
- Hands-on and strong project experience in developing computer vision applications using Framework and Image Libraries: Open CV, TensorFlow, Keras, Scikit-image, and Pytorch.
- Knowledge and hands-on experience with coding different object detection neural network architectures such as CNN, R-CNN, Fast R-CNN, Faster R-CNN, SSD, and YOLO.
- Experience in life cycle management of AI applications from concept, build, deployment, and management.
- Hands-on experience with AI frameworks or libraries like TensorFlow, Keras, Scikit, Pytorch ... etc.
- 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 and 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.
- Well-versed and proficient in Python, C++ scripting languages
- Experience in industrial computer vision applications using AI for tasks such as object detection and tracking.
- Experience working with GIS aerial drone-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
- Having a personal Github account will be an advantage.
- Having analytical capabilities to support engineering decisions.
- 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.
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