LLM Post-Training Engineer, Research & Product

About the Team Would you like to play a part in shipping groundbreaking technology for Large Language Models and Artificial Intelligence? Join the Multimedia AI team at TikTok! We build, research, and apply LLMs to power our products and impact millions of users. We believe the most interesting and impactful problems in AI arise at the intersection of research and real-world deployment - and post-training is where that intersection is sharpest. You will work with a close-knit team of world-class engineers and scientists to tackle some of the most challenging problems in aligning and improving foundation models. You will have unique opportunities to identify and develop novel post-training techniques that directly improve the experience of millions of users globally. Responsibilities: As an LLM Post-training Engineer, you will play a critical role in driving post-training strategies across various LLMs and product areas. Your work will directly shape the behavior, safety, and quality of our foundation models. - Lead efforts in instruction tuning, preference tuning, and model alignment to ensure models are helpful, safe, and performant in real-world applications. - Drive technical roadmaps and propose your own research agenda to advance the state-of-the-art in post-training methodologies. - Tackle complex problems in reward modeling, human preference learning, and the evaluation of model behavior across diverse product use cases. - Provide technical mentorship and guidance to the team, fostering a culture of engineering excellence and rapid innovation. - Collaborate closely with cross-functional engineering and product teams to integrate advanced LLM capabilities into the TikTok ecosystem. - Drive execution on large-scale training pipelines and optimization strategies to bridge the gap between theoretical research and production-ready AI. @@HD@@ Qualifications@@/HD@@ Minimum Qualifications: - BS or MS in Machine Learning, Computer Science, or a related technical field. - Demonstrated expertise in bridging the gap between research and product innovation. - Proven and consistent track record of forming partnerships to solve complex technical problems at scale, ideally for products with a global customer base. - Strong proficiency in deep learning frameworks and experience with large-scale distributed training. Preferred Qualifications: - Specialized expertise in LLM Post-training. - Experience with reward model design, evaluation benchmarks, and red-teaming for LLM safety. - Contributions to the research community or significant contributions to open-source LLM projects. @@HD@@- Ability to thrive in a fast-paced environment and manage evolving priorities. Job Information@@/HD@@ @@HD@@ [For Pay Transparency] Compensation Description (annually)@@/HD@@ The base salary range for this position in the selected city is $212800 - $450000 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units. Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure). The Company reserves the right to modify or change these benefits programs at any time, with or without notice. For Los Angeles County (unincorporated) Candidates: Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: 1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues; 2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and 3. Exercising sound judgment.