Responsibilities

Our Business Integrity team has a strong user focus and a dedication to technical excellence. We aim to meet our users' needs with reliable and high-performing platforms and services. We are looking for strong machine learning engineers who are excited to grow their business understanding, build highly scalable machine learning models, and partner across disciplines with global teams, in pursuit of excellence. Given the fast growth of TikTok in the world, we are working on building a next-generation content understanding system for TikTok monetization. We are seeking Research Engineers who are experienced in machine learning, which can help us create an ecosystem that rewards high quality user experience and advertiser value. Responsibilities 1. Research and develop cutting-edge generative AI technologies, including LLMs, multimodal models (text/image/video), and deepfake detection/synthesis, optimizing performance across pre-training, SFT, RLHF, and AI safety. 2. Design and deploy AIGC solutions for content understanding and monetization in ads, e-commerce, short video, and live streaming, building next-gen AI-driven ecosystems. 3. Advance LLM-based agents with reinforcement learning, enabling autonomous reasoning, planning, and interactive capabilities for real-world applications. 4. Improve efficiency of large-scale model training and inference, exploring techniques like distillation, quantization, and speculative decoding for scalable deployment. 5. Collaborate cross-functionally to productionized research breakthroughs, ensuring robustness, low-latency, and cost-effective AI services. 6. Stay ahead of industry trends, contributing to patents, publications, and open-source projects in generative AI.

Qualifications

Minimum Qualifications: - MS or PhD in Computer Science, AI, Machine Learning, or related fields (or equivalent industry experience) - Solid transferrable experience in deep learning, NLP, and generative models (LLMs, diffusion models, etc.) - Hands-on experience with large-scale model training, RLHF, and multimodal learning - Proficiency in PyTorch, JAX, or TensorFlow, and familiarity with distributed training frameworks Preferred Qualifications: - Knowledge of AI safety, alignment, and adversarial robustness - Experience in building agentic systems with reinforcement learning. - Strong engineering skills for deploying models at scale.

Job Information

[For Pay Transparency]Compensation Description (Annually)

The base salary range for this position in the selected city is $156000 - $316800 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.