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Tencent Holdings · London

# Senior Researcher, Natural Language Processing

London Senior individual contributor Research & Science 

Listed on Tencent Holdings’s official careers site. Listed as of October 19, 2026. Check that it is still open and apply there.
[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=1947255265967603712)

[OpenNash Jobs](https://jobs.opennash.com/) / [Tencent Holdings](https://jobs.opennash.com/companies/tencent-holdings/) / Senior Researcher, Natural Language Processing

## Job description

### Responsibilities
- Responsible for NLP research and development including LLM reasoning, conversational agents, machine translation, part-of-speech tagging, sentence analysis and named entity recognition.
- Optimize existing online algorithms, develop efficient and reliable NLP solutions by combining business needs and data.
- Explore applications of NLP techniques and deep learning algorithms in games.
- Follow the latest developments in academia and industry and quickly apply findings in your work.

### Work Location

UK-London Requirements
- Familiar with NLP fundamentals, with a strong understanding of statistical models, related machine learning principles, and experience working on NLP related projects.
- Proficient in at least one programming language, familiar with basic data structures and algorithms.
- Practical experience working with large language models (e.g., DeepSeel, Qwen, LLaMA), including model fine-tuning, instruction tuning, and evaluation. Familiarity with training optimization frameworks like DeepSpeed, FSDP, and LoRA is highly preferred.
- Experience using tools and frameworks such as LLaMAFactory, Hugging Face Transformers, LangChain, or OpenLLM for model deployment, serving, or pipeline development. Comfortable with using modern MLOps practices for NLP workflows.
- Demonstrated ability to publish research results in top-tier NLP conferences (e.g., ACL, EMNLP, NAACL, NeurIPS, ICLR) or practical contributions to open-source LLM/NLP projects is preferred.
- Comfortable with both classical (e.g., CRF, SVM) and deep learning approaches (e.g., Transformers, RNNs, CNNs, LSTMs, GANs). Deep understanding of transformer architectures, attention mechanisms, and distributed training techniques is a strong advantage. #LI-RL1

## At a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Jul 19, 2026
- Last checked: Oct 19, 2026
- Listed for: 92 days
- Location: London[Apply on Tencent Holdings’s careers site →](https://careers.tencent.com/en-us/jobdesc.html?postId=1947255265967603712)

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