SynaXG Hiring! Full Time AI Engineer — Vision AI - Edge Intelligence in - Ricebowl

We are seeking a talented AI Engineer to develop and deploy Vision AI and Edge Intelligence solutions for real-time, low-latency applications.

The role focuses on designing, implementing, optimizing, and deploying production-grade AI systems across computer vision, multimodal intelligence, and edge inference. The ideal candidate has hands-on experience delivering commercial Vision AI solutions and is passionate about building scalable, high-performance AI applications for real-world environments.

• Develop computer vision models for object detection, segmentation, tracking, video analytics, and scene understanding.
• Implement and optimize Vision AI algorithms for commercial applications across diverse edge deployment scenarios.
• Fine-tune and adapt vision-language models (VLMs) and multimodal large language models (MLLMs) for domain-specific image and video understanding use cases.
• Develop Vision Agent capabilities that combine perception models, multimodal reasoning, natural-language interaction, and tool-based workflows for live or recorded video streams.
• Build and optimize low-latency AI inference pipelines using TensorRT, ONNX Runtime, or similar production inference frameworks.
• Support end-to-end AI deployment, including model integration, validation, performance tuning, and production rollout.

• Strong background in computer vision, deep learning, and AI application development.
• Proficiency in PyTorch, TensorFlow, or equivalent deep learning frameworks.
• Hands-on experience with object detection, segmentation, tracking, video analytics, or related Vision AI applications.
• Knowledge of MLLMs, VLMs, and foundation model adaptation for image, video, and text-based multimodal understanding.
• Practical experience deploying AI models using ONNX, TensorRT, or similar inference optimization frameworks.
• Hands-on experience with NVIDIA Metropolis and related vision AI deployment stacks such as DeepStream, TensorRT, or GPU-accelerated video analytics pipelines.
• Proven experience developing and deploying commercial Vision AI solutions in production environments.
• Strong programming skills in Python and familiarity with C++ for AI application development.

• Experience with multimodal learning, vision-language models (VLMs), multimodal large language models (MLLMs), or foundation model adaptation.
• Familiarity with Vision Agent concepts such as video question answering, video summarization, visual grounding, multimodal RAG, agentic tool use, and real-time interaction with video streams.
• Experience with NVIDIA AI software stack, including CUDA, TensorRT, DeepStream, or related GPU acceleration technologies.
• Familiarity with NVIDIA Isaac, NVIDIA Cosmos, and NVIDIA Omniverse for robotics, Physical AI, simulation, synthetic data, or digital-twin workflows is desired.
• Experience with Docker, Kubernetes, or containerized AI deployment.
• Background in real-time video processing, telecom systems, robotics, smart surveillance, autonomous systems, or Physical AI applications.

• Bachelor's degree or higher in Computer Science, Artificial Intelligence, Electrical Engineering, or a related technical field.
• Strong foundation in machine learning, deep learning, computer vision, or applied mathematics.

• Minimum 3 years of relevant industry experience in AI, Machine Learning, or Computer Vision.
• Demonstrated experience developing and deploying production-grade Vision AI systems for commercial applications.
• Experience delivering AI solutions from model development through deployment and production support is an advantage.