You will be part of a large team of research engineers and work on developing large language models specialized to meet the customers' specific needs. You are expected to lead portions of this team in research and development tasks such as supervised fine-tuning (SFT), reinforcement learning (RLHF, DPO), retrieval-augmented generation, as well as more advanced tasks at the cutting edge of research. You are expected to provide feedback and direction to the data engineering team regarding data collection, cleaning, and processing, and also to collaborate with the annotation team regarding the evaluation of the large language model. Being a senior engineer, you will spend time leading and mentoring junior research engineers to complete their tasks.
Requirements
1. At least 5 Years of Experience on Machine/Deep Learning Projects
- A minimum of 5 years of experience in machine learning projects (CV, RecSys, or others), including 2 years of specialized work with large language models (LLMs).
- Training and deploying models on online service systems, and solving accuracy and latency issues
- Experience on e2e Agent and Rag solution designs and development.
- Ability to make e2e bad case and root cause analysis, and to solve them
2. Large Language Models
- Knowledge on SOTA LLM architectures
- Supervised Fine-Tuning of LLMs (SFT)
- Reinforcement Learning (PPO, GRPO)
- In-context Learning (prompt engineering)
- Alignment (e.g. RLHF-PPO, DPO)
- PyTorch, Pandas, NumPy
3. Natural Language Processing
- Data Collection and Preprocessing
- Text Representation (e.g. BoW, word embeddings, contextual embeddings)
- Neural Network Architectures used in NLP.
- Language Models (n-gram, masked, causal, encoder-decoder)
- Experience with common NLP tasks such as spelling correction, text classification, token classification (NER, POS, etc.), machine translation.
4. Academic Credentials
- Master’s or Ph.D. in Computer Engineering or related fields.
- Ability to read and implement SoTA LLM papers.
- Willingness to follow NLP and LLM literature and stay informed of the latest developments.
- Publications in reputable conferences and journals.
5. Non-technical Requirements
- Fluency in written and spoken English.
- Strong communication and leadership skills.
Benefits
- A real job from day one: We offer you a professional career in one of the leading multinational technology companies.
- Local & international: Reaching more than 190 countries, Huawei is a successful and respected business. We focus on the needs of local customers by harnessing global expertise and teamwork. For you, that means exceptional exposure and experience.
- Great Development Opportunities: We'll support you every step of the way, with hands-on experience which includes functional, cross-functional, and international rotations.
- Fast growth and ambitious vision.
- Learning and Development opportunities.
