Job
Description
Experience: 3+ yrs Location: Delhi, India (On-site) Job Description Hypervise by Eternal Robotics is a cutting-edge industrial AI platform that enables real-time quality inspection, process control, and defect detection through advanced computer vision and deep learning technologies. We serve sectors such as automotive, apparel manufacturing, pharmaceuticals, and packaging by digitizing production lines and delivering operational efficiency through AI. Role Overview We are seeking a highly skilled and proactive Lead Engineer – Computer Vision to architect and lead the development of AI-powered inspection systems and edge deployments. This is a mission-critical role responsible for delivering robust, production-grade computer vision solutions while leading junior engineers across projects and deployments. The ideal candidate thrives in a fast-paced environment, combines strong technical execution with cross-functional collaboration, and has a passion for solving real-world industrial problems using vision AI. Key Responsibilities 1. Project Management & Technical Leadership Lead and monitor end-to-end execution of CV/AI projects, from requirement gathering to final deployment. Collaborate with cross-functional teams (Product, Hardware, QA, Customer Success) to align project milestones. Regularly update stakeholders and prepare detailed technical and status reports. 2. Client Engagement & Time Management Engage with customers to understand and translate use-case requirements into engineering specifications. Manage expectations on delivery timelines and provide technical demonstrations or updates. Support sales/pre-sales efforts with feasibility analysis, proof-of-concept (PoC) development, and architecture design. 3. CV Pipeline Development & Code Quality Design scalable and reusable CV pipelines using best practices in modular software architecture. Lead code reviews and mentor junior team members to ensure consistency and maintainability. Integrate components including ML models, camera streams, and decision layers. 4. Model Development & Optimization Train, evaluate, and optimize object detection, classification, and segmentation models. Utilize frameworks such as TensorFlow, PyTorch, and OpenCV, with an emphasis on YOLO, DeepStream, and Jetson-compatible models. Implement pre- and post-processing pipelines to address challenging industrial imaging conditions. 5. Testing, QA & Deployment Create test cases and validation protocols to verify system performance against customer specs. Supervise on-site and remote deployments; ensure robust integration of edge devices like Jetson Xavier/Nano and industrial cameras. Provide deployment support including remote debugging, calibration, and performance tuning. 6. Continuous Improvement & Innovation Experiment with state-of-the-art models and libraries to enhance detection accuracy and reduce latency. Identify and act on opportunities to improve system resilience, processing speed, and resource utilization. Contribute to IP generation and internal technical documentation. Key Performance Indicators (KPIs) Model Accuracy: Precision and recall metrics in real production environments System Deployments: Number and success rate of on-time installations Resolution Time: Average TAT for solving deployment or inference issues On-Time Delivery: Project milestone adherence across sprints Quality of Deliverables: Based on code audits, testing coverage, and system stability Customer Feedback: Direct user feedback and CSAT/NPS post-deployment Required Qualifications & Experience Education: Bachelor’s degree in Electronics, Computer Science, or a related field. Advanced degrees or certifications in AI/ML are a plus. Experience: 3+ years of hands-on experience in developing computer vision solutions, ideally in manufacturing, robotics, or industrial automation. Domain Knowledge: Experience with industrial cameras, inspection systems, and edge computing setups is highly preferred. Technical Skills Languages: Python (primary), C++ (desirable) Frameworks/Libraries: OpenCV, TensorFlow, PyTorch, YOLO, DeepStream Edge Computing: Jetson Nano/Xavier, deployment on embedded devices Operating Systems: Linux (Ubuntu preferred), bash scripting Integration: ROS, MQTT, GStreamer, Modbus/TCP/IP DevOps: Git/GitHub, Docker, CI/CD familiarity Tools: VS Code, Jupyter, NVIDIA Nsight, camera SDKs (FLIR, Basler, IDS, etc.) Soft Skills Strong analytical and debugging skills with a detail-oriented mindset Clear and concise communication across technical and non-technical teams Ownership mindset with the ability to lead and mentor junior engineers Comfortable in agile, deadline-driven environments and willing to take initiative Why Join Us? Build real-world AI systems that impact global production lines Work in a cross-disciplinary team of engineers, designers, and domain experts Fast-track your growth in a company at the forefront of AI transformation in manufacturing Access cutting-edge tools, datasets, and continuous learning opportunities
