At a Glance
- Tasks: Lead cutting-edge NLP research and develop innovative solutions for real-world applications.
- Company: Join a forward-thinking tech company that values 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 an impact in the exciting field of NLP and work with the latest technologies.
- Qualifications: Strong background in NLP, machine learning, and programming skills required.
The predicted salary is between 63000 - 77000 £ 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.
- 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.
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., Deep Seel, Qwen, LLa MA), including model fine-tuning, instruction tuning, and evaluation.
Familiarity with training optimization frameworks like Deep Speed, FSDP, and Lo RA is highly preferred.
- Experience using tools and frameworks such as LLa MAFactory, Hugging Face Transformers, Lang Chain, or Open LLM 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, Neur IPS, 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.
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Senior Researcher, Natural Language Processing employer: Lightspeed Studios
At Lightspeed Studios, we pride ourselves on fostering a dynamic and inclusive work culture that encourages creativity and innovation. As a Gaming Market Research Intern in London, you'll have the opportunity to collaborate with passionate professionals, gain hands-on experience in data analysis, and contribute to exciting game development projects. We offer robust mentorship and growth opportunities, ensuring that your internship is not just a job, but a stepping stone towards a rewarding career in the gaming industry.
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We think this is how you could land Senior Researcher, Natural Language Processing
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We think you need these skills to ace Senior Researcher, Natural Language Processing
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
