Senior Applied Scientist, Large Language Models
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Job Summary
We are looking for a Senior Applied Scientist to develop advanced large language model capabilities for complex knowledge-intensive applications.
You will work across applied research model development evaluation and product implementation. The role requires both strong algorithmic foundations and the ability to translate emerging AI technologies into reliable scalable product capabilities.
You will collaborate closely with engineering product data and domain teams to identify high-value algorithmic problems and drive solutions from experimentation to production.
- Research and develop large language model capabilities for real-world applications.
- Improve model performance in areas such as reasoning long-context understanding information extraction retrieval-augmented generation and domain adaptation.
- Design and implement model post-training approaches including supervised fine-tuning preference optimization knowledge distillation and synthetic data generation.
- Develop systematic evaluation methodologies covering accuracy factuality robustness safety latency and cost.
- Build scalable data preparation model experimentation and evaluation pipelines.
- Analyse model failure cases and identify effective approaches for continuous improvement.
- Explore emerging research and assess its practical value in production environments.
- Work with engineering teams to deploy and optimize models and AI capabilities in production.
- Collaborate with product managers and domain experts to translate business requirements into algorithmic solutions.
- Contribute to technical standards best practices and the longer-term development of the AI technology roadmap.
- Provide technical guidance and support to other algorithm engineers and researchers.
- Masters degree or PhD in Computer Science Artificial Intelligence Machine Learning Natural Language Processing or a related discipline or equivalent practical experience.
- Strong experience in machine learning natural language processing or applied AI.
- Hands-on experience developing or adapting large language models.
- Strong understanding of Transformer architectures model training fine-tuning and inference.
- Practical experience in at least two of the following areas:
- LLM post-training and alignment
- Model evaluation and benchmarking
- Retrieval-augmented generation
- Long-context modelling
- Information extraction
- Complex reasoning and planning
- Model compression or inference optimization
- Strong proficiency in Python and deep learning frameworks such as PyTorch.
- Ability to independently define algorithmic problems design experiments analyse results and deliver production-ready solutions.
- Strong communication and cross-functional collaboration skills.
- Experience developing AI solutions for enterprise scientific technical or other knowledge-intensive applications.
- Experience with distributed training large-scale inference or GPU optimization.
- Experience building automated evaluation systems data flywheels or human-feedback pipelines.
- Experience with multimodal models AI agents or tool-augmented language models.
- Publications in reputable AI machine learning or NLP conferences or meaningful open-source contributions.
Required Experience:
Senior IC
About Company
Patsnap empowers IP and R&D teams with advanced AI to get better answers and make faster decisions. Increase IP productivity by 75% while reducing R&D wastage by 25%.
