Research Scientist - Driven Agent Self-Evolution - Global Frontier Tech Recruitment Program - 2[...]

Research Scientist - Driven Agent Self-Evolution - Global Frontier Tech Recruitment Program - 2027 Start (PhD) Location: Seattle Team: Technology Employment Type: Regular Job Code: A204608 Responsibilities Research and develop agent frameworks that continuously learn and improve from execution traces, user feedback, and environmental signals. Build large‑scale log analytics pipelines to extract quality signals, usage patterns, and actionable insights from model and agent invocation logs, driving data‑informed system and model improvements. Explore and apply frontier techniques in LLM post‑training, reasoning, and planning to enhance agent capabilities. Collaborate across algorithm research, platform engineering, and product teams to turn research ideas into production‑grade systems at scale. Qualifications Minimum Qualifications : Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related discipline. Strong theoretical and practical foundation in machine learning, deep learning, reinforcement learning, or optimization. Research experience in at least one of the following areas: LLM‑based agents, planning and reasoning, multi‑agent systems, continual/lifelong learning, or LLM post‑training (e.g., RLHF, DPO, GRPO, self‑play). Strong programming skills in Python and proficiency with ML frameworks (e.g., PyTorch, TensorFlow, JAX). Publication record at top‑tier venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI, AAMAS, COLM). Strong problem‑solving skills and ability to thrive in a fast‑paced, collaborative environment. Preferred Qualifications : Publications in areas directly related to agent learning and adaptation, such as tool use, self‑improvement, skill discovery, trajectory optimization, reward modeling, or agent evaluation. Research experience in LLM reasoning and planning, including chain‑of‑thought, tree/graph search, Monte Carlo methods, or inference‑time compute scaling. Experience training or fine‑tuning large language models, including supervised fine‑tuning, preference optimization, or curriculum learning. Hands‑on experience building or evaluating LLM‑based agent systems (e.g., ReAct, function calling, code generation agents, or multi‑agent orchestration). Familiarity with meta‑learning, few‑shot generalization, or transfer learning in the context of LLM‑based systems. Experience with feedback‑driven optimization loops, such as online learning, bandit methods, or evolutionary strategies applied to agent improvement. Strong interest in bridging frontier AI research with production‑grade engineering — turning papers into systems that work at scale. Internship experience at technology companies or research organizations. Job Information The base salary range for this position in Seattle is $202,160 - $368,220 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. 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 include 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, 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. Legal and Equity Statements 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. 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: Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues; Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; Exercising sound judgment. Reasonable accommodations in our recruitment processes are available for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If assistance or a reasonable accommodation is needed, please reach out to us at #J-18808-Ljbffr ByteDance