Linker Vision 專注於開發自駕、工安以及公衛醫療領域的AI平台。由一群對於人工智慧發展充滿熱誠的年輕人組成，我們擁有開放的組織文化以及敏捷的開發團隊，若你也想要一同和我們開創人工智慧的新時代，加入Linker絕對是你的最佳選擇。
▋What's it like to be a Linker?
You will be working with a talented team to build a promising computer vision AI development platform. You will learn from our global clients their pain points and create solutions for them. You'll see how we managed to process tremendous real-world data to build computer vision models and applications for maximal impact. You will have a unique chance here to grow your desired career.
▋We’re looking for a Machine Learning Engineer to help us deploy highly efficient and robust machine learning models and build the most intelligent software stack for our computer vision-related applications
▋What you will do:
▸ Design and develop robust software for executing Deep Learning Inference on hardware accelerators
▸ Build the production level video stream pipeline (GStreamer, Nvidia DeepStream, Intel DLStreamer)
▸ Analyze and optimize the performance of ML models on difference accelerators
▸ Collaborate with PMs and Data Scientists to guide the direction of inferencing
▋What you must have:
▸ MS or higher degree in CS/CE/EE, or equivalent in industry experience
▸ +1 Year of experience in the field of Machine Learning deployment
▸ You should be comfortable writing production-level c/c++ codes
▸ You should be familiar with system programming on Linux
▸ You should be familiar with performance analysis, debugging, and optimization
▸ Extensive experience with Computer Vision related algorithms/models (e.g. CNN, Object Detection, Tracking, …)
▸ Extensive experience with ML accelerators (e.g. GPU, VPU, …)
▸ Extensive experience with ML inference software (e.g. TensorRT, TFLite, OpenVINO)
▸ Extensive experience with ML training frameworks (e.g. TensorFlow, PyTorch, …)
▋Nice to have:
▸ Experienced in GPU programming (e.g. CUDA, OpenCL)
▸ Experienced in ML deployment on inference SDK (e.g. TensorRT, OpenVINO)
▸ Familiar with Python
▸ Familiar with OpenCV
▸ Familiar with Video Stream software (e.g. Gstreamer, FFMPEG, Deepstream, DLStreamer)
We do our best to plan, but we also understand that keeping up with changes is challenging. Therefore, managing chaos is significant, particularly when growing a business.
Hacker spirit is within everyone's blood, not just engineers. We always find ways to unblock obstacles, make things work, and hold ourselves accountable for the result.
One man alone may have blind spots. That's why we need to team up and rely on each other.
Stage 1. HackerRank Coding Test (1h)
Stage 2. RD Manager (1h)
Stage 3. CTO (1h)
Stage 4. CEO (40mins-1h)
我們致力於加速 AI 電腦視覺應用的開發，以自動標註系統來克服深度學習中最困難的挑戰 - 準備高品質的訓練資料。除此之外，我們建立 AI 電腦視覺模型持續學習機制以適應新的資料變化，透過優化整體開發流程，從資料攝取及篩選、模型訓練及驗證、到佈署及監控，讓 AI 電腦視覺能更快速簡易地持續學習。