- Build and optimize deep learning models for object detection, segmentation, and classification.
- Use frameworks like YOLO, OpenCV, TensorFlow, and PyTorch to deliver high-performing models.
- Validate model accuracy against customer specifications and datasets.
- Develop modular and maintainable computer vision pipelines using Python.
- Integrate pre-processing, inference, and post-processing components for edge and server-side deployments.
- Work with industrial cameras, Jetson edge devices, and Linux-based systems for field deployment.
- Support hardware selection and calibration, assist with on-site installations and provide deployment troubleshooting.
- Write and execute test cases to ensure system functionality and robustness in diverse environments.
- Collaborate with QA and support teams to resolve performance issues.
- Document architecture, model performance, and system configurations.
- Participate in code reviews and peer programming sessions.
- Coordinate with team leads and project managers to align with delivery timelines.
- Education: Bachelor's in Computer Science, Electronics, or related engineering field. Master's degree or certifications in AI/ML is a plus.
- Experience: 3–6 years of hands-on experience in computer vision development, preferably in industrial or real-time environments.
- Proficiency in Python and OpenCV.
- Experience with deep learning libraries: PyTorch, TensorFlow, Keras.
- Familiarity with YOLO models (v5/v8), CNNs, object tracking, and segmentation.
- Working knowledge of Linux environments, Git, and basic shell scripting.
- Experience with Jetson Nano/Xavier, DeepStream SDK is preferred.
- Understanding of camera configuration, lighting setups, and imaging constraints.
- Experience deploying models on edge or embedded devices is a strong advantage.
- Strong debugging and problem-solving skills.
- Team player with a willingness to learn and adapt.
- Effective communicator capable of interfacing with both engineering and customer teams.
- Disciplined in documentation and reporting.
- Build solutions that are deployed across real industrial environments.
- Work alongside passionate technologists in a startup culture.
- Access to advanced tools, data, and edge-AI hardware.
- Be part of a company leading the industrial AI revolution.
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Computer Vision Engineer - Pune - Eternal Robotics
Description
About Eternal Robotics – Hypervise
Hypervise is the flagship industrial AI platform of Eternal Robotics, built to transform real-time quality inspection and automation through advanced computer vision and edge AI. Our clients span automotive, apparel, pharmaceuticals, and more — industries where speed, accuracy, and reliability are mission-critical.
Role Overview
We are looking for a AI Engineer - Computer Vision with 3-6 years of experience to develop and deploy production-grade CV solutions across our customer sites. This role combines hands-on development of models and algorithms with end-to-end ownership of system integration, testing, and deployment in real-world industrial environments.
You will work closely with senior engineers, product leads, and customer teams to bring CV/AI projects to life and continuously improve solution performance.
Key Responsibilities
1. Model Development & Testing
2. CV Pipeline Implementation
3. Hardware & Deployment Support
4. Testing & Quality Assurance
5. Documentation & Collaboration
Qualifications & Experience
Key Technical Skills
Soft Skills
Why Join Hypervise?
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Computer Vision Engineer
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Computer Vision Engineer
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Senior Computer Vision Engineer
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AI Computer Vision Engineer
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Machine Vision Engineer
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AI Computer Vision Engineer Associate
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Senior Computer Vision Machine Learning Engineer
Only for registered members Maharashtra, Pune, India
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Computer Vision Engineer Technical Pre-Sales
Only for registered members Pune
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Systems - Machine Learning Engineer - Computer Vision
Only for registered members Pune, Maharashtra
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CCTech - Artificial Intelligence Engineer - NLP/Computer Vision
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AI Engineer
Full time Only for registered members Pune-Maharashtra-India
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Software Engineer
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