Computer Vision & Edge AI Engineer
Hạn nộp hồ sơ: 30/11/2026 (Còn 15 ngày)
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Job Description
- Research, design, and develop AI solutions for company projects and products in Computer Vision, video analytics, Edge AI, robotics, and smart factory domains.
- Build and maintain end-to-end Computer Vision pipelines, including camera or video stream ingestion, preprocessing, model inference, object tracking, post-processing, event generation, system integration, and result validation.
- Develop, train, evaluate, and optimize AI models for use cases such as object detection, object tracking, image classification, segmentation, human and obstacle detection, industrial inspection, and camera-based localization.
- Work with Computer Vision and AI technologies such as OpenCV, PyTorch, TensorFlow, ONNX Runtime, YOLO, or equivalent frameworks and solutions.
- Integrate AI models with IP cameras, RTSP video streams, recorded video, GPU servers, and edge devices.
- Develop and optimize real-time or near-real-time video processing pipelines for single-camera and multi-camera systems.
- Monitor and optimize inference performance, including FPS, latency, GPU utilization, memory consumption, throughput, and system stability.
- Analyze technical bottlenecks across camera ingestion, video decoding, preprocessing, inference, tracking, and downstream integration.
- Apply model optimization and deployment technologies such as ONNX, TensorRT, NVIDIA DeepStream, GStreamer, or equivalent solutions when appropriate.
- Develop AI services, backend APIs, or microservices to integrate AI capabilities into production systems.
- Collaborate with Backend, Frontend, Robot Control, Quality Engineering, and Infrastructure teams to deliver end-to-end AI applications.
- Work closely with Business Analysts and Project Managers to understand requirements, define technical assumptions, identify risks, and establish acceptance criteria.
- Review existing AI architectures, source code, and pipelines, and propose improvements related to performance, scalability, maintainability, reliability, and operating cost.
- Monitor model and system performance, analyze errors, and propose improvements to increase accuracy and operational stability.
- Prepare and maintain technical documentation, benchmark reports, deployment guides, troubleshooting guides, and reusable AI components.
- Support knowledge sharing, code review, and technical guidance for other AI engineers.
- Participate in technical discovery, feasibility assessment, proof-of-concept planning, and solution proposal activities after the onboarding and training period.
- Explain technical approaches, limitations, assumptions, and validation requirements clearly to internal teams and customers.
- Collaborate with LLM and Intelligent Document Processing teams for multimodal or cross-domain AI use cases when required.
- Ensure AI solutions comply with data security, access control, system reliability, and information security requirements.
Qualifications
- Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field.
- Minimum 5 years of hands-on professional experience primarily focused on Computer Vision, Edge AI, real-time video analytics, or closely related applied AI areas.
- For candidates transitioning from Software Engineering, Backend, Embedded, or Full-stack development, minimum 7 years of total professional engineering experience is required, including at least 3 years of hands-on production experience in Computer Vision or Edge AI.
- Strong Software Engineering foundation and experience developing AI features beyond research notebooks or standalone experiments.
- Strong Python programming skills.
- Hands-on experience with one or more Computer Vision use cases, such as object detection, object tracking, image classification, image segmentation, video analytics, human or obstacle detection, or industrial image inspection.
- Experience with AI and Computer Vision frameworks such as OpenCV, PyTorch, TensorFlow, ONNX Runtime, YOLO, or similar technologies.
- Experience integrating AI models into applications, backend services, APIs, microservices, or production systems.
- Understanding of model evaluation metrics such as accuracy, precision, recall, F1-score, mAP, false positive rate, and false negative rate.
- Experience analyzing model performance in real-world environments, not only on offline datasets.
- Familiarity with Linux, Git, Docker, and standard software development practices.
- Familiarity with REST APIs, backend integration, databases, message queues, or system-to-system communication.
- Ability to analyze technical issues, identify root causes, and troubleshoot complex AI or software problems.
- Ability to understand system architecture and work across model, application, integration, and deployment layers.
- Strong analytical, problem-solving, self-learning, and ownership skills.
- Good communication skills and the ability to explain technical issues in a clear and structured manner.
- Ability to read technical documentation in English and work effectively with cross-functional teams.
Nice to have
- Experience with NVIDIA DeepStream, GStreamer, TensorRT, CUDA, or GPU profiling tools.
- Experience processing RTSP streams, IP camera feeds, recorded video, or multi-camera systems.
- Experience with real-time video analytics, hardware-accelerated video decoding, frame synchronization, stream reconnection, or video pipeline optimization.
- Experience deploying AI workloads on NVIDIA GPU servers, NVIDIA Jetson devices, or other Edge AI platforms.
- Experience with ONNX conversion, FP16 or INT8 optimization, model quantization, or inference acceleration.
- Experience with C++ for Computer Vision, video processing, or high-performance AI applications.
- Experience with FastAPI, Flask, Django, [protected info], Java, Go, Rust, or equivalent backend technologies.
- Familiarity with WebSocket, MQTT, Kafka, RabbitMQ, Redis, or other message-based integration technologies.
- Experience with smart factories, industrial cameras, robotics, AMR, AGV, PLC, Remote I/O, or industrial automation systems.
- Experience with camera calibration, coordinate transformation, AprilTag, ArUco markers, or camera-based robot localization.
- Experience building monitoring dashboards, operator HMI, or visualization systems for AI and robotics applications.
- Experience with Kubernetes, CI/CD pipelines, cloud platforms, on-premises deployment, or infrastructure monitoring.
- Experience with LLMs, VLMs, RAG, Document AI, OCR, NLP, vector databases, prompt engineering, agent workflows, or multimodal AI applications.
- Experience integrating Computer Vision results with LLM-based or Intelligent Document Processing solutions.
- Experience participating in technical workshops, customer meetings, solution consulting, or technical pre-sales activities.
- Ability and willingness to develop toward a technical ownership, technical lead.
What we offer?
- Attractive salary, suitable for working capacity
- Review performance twice a year (In working process, Candidate can be reviewed continuously before the term if the job is successfully completed)
- Devices provided (Laptop, PC, mouse, monitor...)
- Working hours: HN, Vinh: 8:30 - 17:30, HCM: 9:00 -18:00, 5 days/ week.
- Enjoying good remuneration of company when becoming an employee: social insurance, PTI insurance, annual company trip,...
- Recognition and rewards based on your performance
- High promotion opportunity
- Good career path development
- Creative, modern and open working place
- Continuous and professional training to fully develop your potential
Thông tin chung
- Thu nhập: Thỏa thuận
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Thông tin công việc
Vị trí:
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Hình thức làm việc:
Toàn thời gian
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