
Principal Applied Scientist
- Suzhou, Jiangsu
- Permanent
- Full-time
- Research, design, and prototype methods to leverage LLMs for product scenarios such as text understanding, summarization, dialogue, translation, content generation, and reasoning.
- Fine-tune, adapt, and optimize pre-trained LLMs for domain-specific tasks while balancing model performance, efficiency, and cost.
- Develop scalable pipelines for data collection, cleaning, augmentation, and evaluation.
- Collaborate with product and engineering teams to translate applied research into production-quality features.
- Define and track key performance metrics for LLM-based features, including accuracy, latency, robustness, and user satisfaction.
- Stay current with advances in generative AI, multimodal models, and applied ML techniques, and bring forward innovative ideas to improve our products.
- Publish technical insights internally (and externally where appropriate) to advance organizational knowledge and thought leadership.
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 5+ years of experience in applied machine learning, natural language processing (NLP), or related domains.
- Strong knowledge of modern NLP methods, particularly transformers, LLMs, and transfer learning.
- Hands-on experience with at least one deep learning framework (e.g., PyTorch, TensorFlow, JAX).
- Proficiency in Python and familiarity with ML tooling, experimentation, and evaluation frameworks.
- Experience with data preprocessing, feature engineering, and large-scale training/inference.
- Strong analytical and problem-solving skills, with ability to bridge research and product needs.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- MS or PhD in Computer Science, Machine Learning, Statistics, Applied Mathematics, or related field, or equivalent industry experience.
- 7+ years of experience in applied science roles focused on AI/ML or NLP, with a track record of technical excellence and innovation.
- Experience fine-tuning or instruction-tuning large foundation models.
- Knowledge of prompt engineering, retrieval-augmented generation (RAG), or multi-agent LLM systems.
- Familiarity with distributed training, model optimization, and deployment in production systems.
- Track record of published work in ML/NLP conferences or journals.
- Experience working in cross-functional teams, shipping AI-powered features to users.