Lead Computer Vision AI Engineer

NGXP Technologies Location: Kochi – BB Arcade Full Time – Immediate

Job Description

Lead Computer Vision AI EngineerAbout the RoleWe are seeking a highly skilled and visionary Lead Computer Vision AI Engineer to spearhead the development of our enterprise-grade visual intelligence capabilities. In this role, you will architect, build, and scale state-of-the-art computer vision systems that solve complex problems for our internal operations and external client projects. You will not be working in a silo. You will be supported by a robust, cross-functional engineering team—including Full-Stack .NET, Angular, React, and Node.js developers, Database Engineers, Software Architects, Frontend Designers, Flutter Mobile App Developers, and other AI Engineers. Your primary focus will be designing the core vision models, multimodal pipelines, and deployment architectures, ensuring they are scalable, highly accurate, and optimized for both cloud and edge environments.Key Responsibilities

• Architect Advanced Vision Systems: Design and implement state-of-the-art computer vision pipelines utilizing the latest architectures, including Vision Transformers (ViT), Vision-Language Models (VLMs), and multimodal foundation models.
• Develop Reusable CV Assets: Build foundational vision architectures for object detection, segmentation (e.g., SAM, YOLOv8/YOLO-World), and video understanding that can be fine-tuned and deployed across various client projects with minimal friction.
• Multimodal Integration: Leverage Vision-Language Models (e.g., GPT-4V, Gemini, Qwen-VL, LLaVA) to bridge the gap between visual data and natural language reasoning, enabling complex visual Q&A and automated reporting.
• Edge & Cloud Deployment: Optimize models for real-time inference across diverse hardware environments, from high-performance cloud GPUs to edge devices (NVIDIA Jetson, mobile devices) using TensorRT, ONNX, and OpenVINO.
• Cross-Functional Leadership: Collaborate closely with our existing software architects, full-stack developers, and mobile engineers to integrate computer vision capabilities seamlessly into our web and mobile applications.
• MLOps & Continuous Evaluation: Implement robust MLOps pipelines for continuous data ingestion, model retraining, versioning, and observability to monitor model drift and performance in production environments.Required Skills Matrix Skill Category Required Expertise Preferred / Bonus Advanced CV Architectures Deep expertise in Vision Transformers (ViT), CNNs, and modern detection/segmentation models (YOLOv8+, Segment Anything Model - SAM). Experience with 3D computer vision, NeRFs, or spatial computing. Multimodal & VLMs Hands-on experience with Vision-Language Models (VLMs) and multimodal foundation models (e.g., CLIP, LLaVA, Qwen-VL). Fine-tuning VLMs for domain-specific visual reasoning tasks. Model Optimization & Edge Proficiency in model quantization, pruning, and deployment using ONNX, TensorRT, or OpenVINO. Experience deploying models to edge devices (NVIDIA Jetson, iOS/Android via CoreML/TFLite). Programming & Frameworks Expert-level Python, PyTorch, and OpenCV. Familiarity with C++ for high-performance inference, or C#/.NET to interface with our existing teams. Production MLOps Experience with ML lifecycle tools (MLflow, Weights & Biases, DVC) and containerized deployments (Docker, Kubernetes). Building automated data annotation and active learning pipelines. Collaboration Ability to translate complex CV concepts into actionable API contracts for traditional software engineering teams. Previous experience leading a computer vision initiative from zero to production. Why Join Us?
• Massive Leverage: You will have an entire army of skilled developers (.NET, React, Flutter, etc.) ready to build the infrastructure, data pipelines, and UIs around your vision models.
• High Impact: Your work will directly shape the future of our product offerings, bringing advanced visual intelligence to real-world client applications.
• Innovation-First: We prioritize scalable, long-term solutions over quick hacks. You will have the resources to build things the right way, utilizing the latest advancements in AI.How to ApplyPlease submit your resume along with a portfolio, GitHub link, or case studies showcasing any advanced computer vision projects, multimodal systems, or production deployments you have built.