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Research Scientist - LLM Foundation Models
Binance
Job Location
Job Summary
The Research Scientist - LLM Foundation Models role at Binance involves enhancing reasoning and planning throughout the development process of foundation models. The candidate will synthesize large-scale data using methods such as rewriting, augmentation, and generation to improve model capabilities. They will also investigate and implement robust evaluation methodologies to assess model performance. Additionally, they will teach foundation models to use tools, interact with APIs, and code interpreters. The ideal candidate has research experience with RL, LLM, and large-scale model training, proficiency in data structures and fundamental algorithm skills, and excellent problem analysis and communication skills. Binance offers a fast-paced, mission-driven organization with opportunities for career growth and continuous learning.
Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 250 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.
Binance is the leading global blockchain ecosystem and cryptocurrency infrastructure provider whose suite of financial products includes the world’s largest digital-asset exchange.
Our mission is to accelerate cryptocurrency adoption and increase the freedom of money.
If you’re looking for a fast-paced, mission-driven organization where opportunities to learn and excel are endless, then Binance is the place for you.
Responsibilities
- Reasoning and planning for foundation models: Enhance reasoning and planning throughout the entire development process, including data acquisition, model evaluation, SFT, reward modeling, and reinforcement learning, to improve overall performance.
- Synthesize large-scale, high-quality data using methods such as rewriting, augmentation, and generation to improve the capabilities of foundation models in various stages (pretraining, SFT, RL).
- Solve complex tasks using system 2 thinking and leverage advanced decoding strategies such as MCTS, A*.
- Investigate and implement robust evaluation methodologies to assess model performance at various stages.
- Teach foundation models to use tools, interact with APIs, and code interpreters. Build agents and multi-agent systems to solve complex tasks.
Requirements
- Proficiency in research experience with RL, LLM, and familiarity with large-scale model training is preferred.
- Proficiency in data structures and fundamental algorithm skills, and fluency in Python or C++/Java.
- Experience with influential projects or papers in RL, NLP, or Deep Learning is preferred.
- Excellent problem analysis and problem-solving skills, capable of deeply addressing challenges in large-scale model training and application.
- Good communication and collaboration skills, with the ability to explore new technologies with the team and promote technological progress.
Why Binance
• Shape the future with the world’s leading blockchain ecosystem
• Collaborate with world-class talent in a user-centric global organization with a flat structure
• Tackle unique, fast-paced projects with autonomy in an innovative environment
• Thrive in a results-driven workplace with opportunities for career growth and continuous learning
• Competitive salary and company benefits
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.
By submitting a job application, you confirm that you have read and agree to our Candidate Privacy Notice.
