Machine Learning Engineer - LLM, AI & Robotics
$148.91k - $252kFull-time
XPENG
XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity. Job Responsibilities
- Fine-tune the pre-trained LLM on particular use cases in Humanoid Robots and Autonomous Driving Cars, e.g. chat, API calling, etc.
- Work on efficient LLMs (e.g. small LLMs, weight sharing, model quantization, etc.) that can be deployed locally in Robots and Cars.
- Develop and maintain the LLM (including multi-modal LLM) training and deployment pipelines that could scale to massive production.
- Work on efficient and effective ways to leverage large scale dataset and computational resource.
- Explore novel ways to generate synthetic data to improve the data diversity & quality.
- Communicate and align with different teams on product needs across the company
- Ph.D in Computer Science or related fields.
- Solid background in machine learning, natural language processing (NLP), computer vision,
- Experience in working with LLMs
- Strong python programming skills & software development, and strong experience with any
- Open-minded, collaborative and excellent communication skills
- Deep understanding of language model modern architectures, ‘under the hood’ LLM training knowledge, quantization techniques, etc.
- Familiarity of large language models (LLMs) relevant technologies, such as SFT, RLHF, prompt engineering, RAG, etc.
- Record of publications, innovations or leadership.
- A fun, supportive and engaging environment
- Opportunity to make significant impact on transportation revolution by the means of
- Opportunity to work on cutting edge technologies with the top talent in the field
- Competitive compensation package
- Snacks, lunches, and fun activities
Vacancy posted 1 day ago
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