AlgorithmEngineer算法工程师

Task Description Research, design, and implement computer vision and vision-language model (VLM) use cases tailored for MBOS. Train and fine-tune deep learning models focusing on multimodal fusion and efficient deployment on embedded platforms. Work closely with software, hardware, and product teams to integrate developed algorithms into the overall vehicle system. Build and maintain toolchains for fine-tuning and deploying LLMs/VLMs, manage training clusters, and ensure efficient inference on both server-side and embedded targets. Experimentation, Evaluation, and Knowledge Transfer to other team members. Qualifications Master degree or above in Computer Science, Electrical Engineering, Robotics, or a related field. Proven hands-on experience in developing and deploying computer vision and/or VLM algorithms, preferably in the automotive or robotics domain. Experience with deep learning frameworks (such as PyTorch, TensorFlow) and classical computer vision libraries Experience with fine-tuning and optimizing LLMs/VLMs (e.g., LoRA, RAG, prompt engineering) Familiarity with multimodal fusion techniques and the architecture of models like Transformer, BERT or similar. Solid grounding in both Natural Language Processing and Computer Vision; able to design and implement solutions that leverage both modalities. Experience with model compression, quantization, and deployment on resource-constrained environments Familiarity with dataset collection, labeling, and evaluation for multimodal tasks Strong programming skills in Python and C++. Experience with cloud services (e.g., Azure, AWS, Tencent) is a plus. Outstanding analytical and problem-solving skills. Technical leadership and ability to make decisions based on technical facts. Strong sense of ownership and drive. Good communication skills and ability to work in a collaborative, cross-functional environment. English proficiency in written and spoken form. Mercedes-Benz Group China Ltd.