Computer Vision Engineer
2 weeks ago
About the Company:
Griphic is founded by IIT Delhi engineers. Our vision is to enrich lives through technological innovation. We combine cutting-edge AI with hyper-realistic virtual experiences to solve problems and bring disruption in the industry. We have a dynamic team with engineers from IIT Delhi, AI/ML engineers, VR developers, and many more. Our startup is backed by the worlds leading design documentation firm, SKETS Studio, which has a strength of 700+ people and specializes in BIM, architecture, VR, and 3D visualization.
Griphic is looking for a Computer Vision Engineer to join our dynamic Cerebrus team. We specialize in conducting meta-human powered and AI-driven interviews. In this role, you will develop and optimize a proctoring model for interview settings, creating AI-driven systems to monitor and analyze candidate behavior while ensuring security and fairness. Your focus will be on detecting suspicious activities, verifying identity, and enabling smooth real-time candidate evaluation.
Key Responsibilities:
- Design and implement computer vision models to monitor candidates during interviews for proctoring purposes.
- Develop algorithms for detecting suspicious behavior, such as cheating or impersonation.
- Optimize models for real-time performance and minimal latency.
- Integrate facial recognition, object detection, and gaze tracking technologies.
- Collaborate with AI and data science teams to improve model accuracy and robustness.
- Continuously monitor model performance and make improvements based on feedback and new data.
- Stay updated on advancements in computer vision, particularly in security and proctoring solutions.
Required Skills:
- Bachelors or Masters degree in Computer Vision, Computer Science, or a related field.
- Proficiency in deep learning frameworks like TensorFlow or PyTorch.
- Strong experience in computer vision techniques (e.g., facial recognition, object detection, gaze tracking).
- Hands-on experience with OpenCV and other vision processing libraries.
- Proficiency in Python and related libraries (NumPy, SciPy).
- Experience with model deployment and optimization for real-time systems.
Interested candidates should submit their resumes at along with a brief cover letter and any relevant project examples or GitHub links.
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