Senior LLM Engineer
SmartAssetFull Time
Senior (5 to 8 years)
Candidates should possess a Master's or Ph.D. in Computer Science, AI, or a related field, along with 5 or more years of experience in machine learning with a focus on NLP and Large Language Models (LLMs). They should have a strong understanding of transformer architectures and modern LLM frameworks such as BERT, GPT, and T5, and demonstrate proficiency in deep learning frameworks like PyTorch, TensorFlow, and JAX. Experience with distributed training systems like Megatron and optimization techniques is also preferred.
The Senior/Machine Learning Engineer (LLM) will engage in the development and optimization of large-scale pre-training language models, including model architecture design, parallel training strategies, and performance improvements. They will drive research and implementation of advanced LLM post-training techniques, such as chain-of-thought tuning and preference alignment. The role involves developing and optimizing data collection pipelines, designing and implementing model deployment solutions, and collaborating with cross-functional teams to apply LLM capabilities in various business scenarios, while staying current with the latest advancements in the field and contributing to the company’s technical roadmap.
Intellectual property and innovation intelligence platform
PatSnap offers a platform that helps businesses, inventors, and researchers understand patents and innovation. Its main product aggregates and analyzes data from patents, scientific literature, and market reports, enabling clients to make informed decisions about their R&D investments. PatSnap operates on a subscription model, providing various service tiers and educational courses to empower clients in leveraging their innovation data. The company's goal is to help clients drive business growth and maintain a competitive edge through effective use of intellectual property.