At a Glance
- Tasks: Lead cutting-edge NLP research and develop innovative solutions for real-world applications.
- Company: Join a forward-thinking tech giant committed to diversity and innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on continuous learning and development.
- Why this job: Make a significant impact in the exciting field of natural language processing.
- Qualifications: Strong background in NLP, machine learning, and programming skills required.
The predicted salary is between 60000 - 80000 £ per year.
Responsibilities
- Responsible for NLP research and development including LLM reasoning, conversational agents, machine translation, part-of-speech tagging, sentence analysis and named entity recognition.
- Optimise 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.
Qualifications
- 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 optimisation 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.
Equal Employment Opportunity
As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.
Senior Researcher, Natural Language Processing employer: Lightspeed Studios
At Tencent, we pride ourselves on being an exceptional employer, particularly for those passionate about advancing Natural Language Processing. Our vibrant work culture encourages innovation and collaboration, providing ample opportunities for professional growth through cutting-edge projects and research initiatives. Located in a dynamic tech hub, employees benefit from a supportive environment that values diversity and fosters creativity, making it an ideal place for meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Researcher, Natural Language Processing
✨Tip Number 1
Network like a pro! Reach out to folks in the NLP community, attend meetups or webinars, and connect with researchers on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your NLP projects, especially those involving large language models. Share your work on GitHub or personal websites, and don’t forget to highlight any publications or contributions to open-source projects.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Be ready to discuss your experience with algorithms, model fine-tuning, and even your favourite NLP breakthroughs. Practice explaining complex concepts in simple terms – it shows you really understand your stuff!
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to reflect how your skills align with our mission and the specific role – it’ll make you stand out from the crowd!
We think you need these skills to ace Senior Researcher, Natural Language Processing
Some tips for your application 🫡
Show Off Your NLP Skills:Make sure to highlight your experience with NLP projects in your application. We want to see how you've tackled challenges like LLM reasoning or conversational agents, so don’t hold back on the details!
Tailor Your Application:Take a moment to customise your application for this role. Mention specific tools and frameworks you’ve used, like Hugging Face Transformers or DeepSpeed, to show us you’re the right fit for our team.
Keep It Professional Yet Personal:While we love a professional tone, don’t be afraid to let your personality shine through. Share your passion for NLP and any exciting projects you’ve worked on – it helps us get to know you better!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining StudySmarter!
How to prepare for a job interview at Lightspeed Studios
✨Know Your NLP Fundamentals
Brush up on your NLP basics before the interview. Make sure you can confidently discuss statistical models, machine learning principles, and your past projects. Being able to articulate your understanding of these concepts will show that you're not just familiar with the field but also passionate about it.
✨Showcase Your Programming Skills
Be prepared to talk about your proficiency in programming languages relevant to NLP. Bring examples of how you've used these skills in real-world projects, especially with large language models. If you’ve worked with frameworks like Hugging Face or LLaMA, make sure to highlight that experience!
✨Stay Updated on Industry Trends
Research the latest developments in NLP and deep learning. Be ready to discuss recent papers or breakthroughs that excite you. This shows that you’re proactive and genuinely interested in advancing your knowledge and skills in the field.
✨Prepare for Technical Questions
Expect technical questions related to algorithms, model fine-tuning, and MLOps practices. Practice explaining complex concepts in simple terms, as this demonstrates your depth of understanding. You might even want to prepare a mini-project or case study to discuss during the interview!
