AI Engineer — Vision AI & Edge Intelligence
Salary: $6,000 – $9,000 per month
Key Responsibilities
Vision AI Development & Edge Real-Time Inference
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.
Required Skills & Experience
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.
Preferred Skills
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.
Education & Qualifications
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.
Experience Requirements
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.