Machine Learning Engineer, TikTok - Business Governance

TikTok Inc.; San Jose (CA); On-site; USD 162,000 - 388,000; Full time

Job summary

TikTok Inc. in San Jose is seeking researchers and engineers to build next-generation Trust & Safety systems across TikTok, Lemon8 and other platforms. You will advance multimodal understanding and risk detection using LLMs, AI agents, and scalable pipelines.

You will train and apply LLMs/MLLMs, explore post-training techniques, and work with cross‑functional teams to deliver robust moderation solutions. The role emphasizes production-ready models and ongoing innovation.

Qualifications

• Bachelor degree or above in Computer Science, Software Engineering, Artificial Intelligence, Mathematics, or related fields
• Strong understanding of machine learning and deep learning, with familiarity with Transformer architectures, LLMs, and MLLMs
• Hands-on experience in Python, PyTorch, distributed training, and large-scale data processing, with solid algorithmic and engineering capabilities
• Proven ability to solve complex problems and collaborate effectively in cross-functional teams, with a track record of driving projects to high-quality execution

Responsibilities

• Develop content safety algorithms for TikTok, Lemon8, and short-form drama platforms, covering multimodal understanding and risk detection across video, text, image, and audio
• Leverage machine learning, deep learning, and large model technologies to improve content moderation pipelines, enhance operational efficiency, and ensure model robustness and production stability
• Own the training and application of LLMs and MLLMs for content safety use cases, including post-training techniques such as SFT, RLHF, DPO, and safety alignment
• Drive the exploration and productionization of emerging capabilities such as AI Agents, multimodal reasoning, and video understanding to build next-generation intelligent moderation systems

Skills

ML foundations

Python

PyTorch

Cross-functional collaboration

Education

Bachelors or above in CS/AI/math

Job description

Responsibilities

About the Team

We are building next-generation Trust & Safety systems powered by large language models and multimodal foundation models to protect TikTok, Lemon8, and short-form video platforms. Our team focuses on multimodal reasoning, content understanding, and large-scale risk detection across text, image, audio, and video. We actively explore and productionize cutting-edge technologies such as LLM post-training, multimodal models, and AI Agents to build intelligent, scalable, and adaptive content moderation systems.

Responsibilities - What You'II Do

• Develop content safety algorithms for TikTok, Lemon8, and short-form drama platforms, covering multimodal understanding and risk detection across video, text, image, and audio
• Leverage machine learning, deep learning, and large model technologies to improve content moderation pipelines, enhance operational efficiency, and ensure model robustness and production stability
• Own the training and application of LLMs and MLLMs for content safety use cases, including post-training techniques such as SFT, RLHF, DPO, and safety alignment
• Drive the exploration and productionization of emerging capabilities such as AI Agents, multimodal reasoning, and video understanding to build next-generation intelligent moderation systems

Qualifications

Minimum Qualifications:

• Bachelor degree or above in Computer Science, Software Engineering, Artificial Intelligence, Mathematics, or related fields
• Strong understanding of machine learning and deep learning, with familiarity with Transformer architectures, LLMs, and MLLMs
• Hands-on experience in Python, PyTorch, distributed training, and large-scale data processing, with solid algorithmic and engineering capabilities
• Proven ability to solve complex problems and collaborate effectively in cross-functional teams, with a track record of driving projects to high-quality execution

Preferred Qualifications:

• Hands-on experience with LLM post-training, multimodal understanding, AI Agents, or Trust & Safety systems is desirable
• Publications in academic conferences such as NeurIPS, ICML, ICLR, CVPR, ECCV, ICCV, ACL, EMNLP, NAACL, Interspeech, ICASSP, and others are a strong plus

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $387600 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.

Responsibilities

About the Team

We are building next-generation Trust & Safety systems powered by large language models and multimodal foundation models to protect TikTok, Lemon8, and short-form video platforms. Our team focuses on multimodal reasoning, content understanding, and large-scale risk detection across text, image, audio, and video. We actively explore and productionize cutting-edge technologies such as LLM post-training, multimodal models, and AI Agents to build intelligent, scalable, and adaptive content moderation systems.

Responsibilities - What You'II Do

• Develop content safety algorithms for TikTok, Lemon8, and short-form drama platforms, covering multimodal understanding and risk detection across video, text, image, and audio
• Leverage machine learning, deep learning, and large model technologies to improve content moderation pipelines, enhance operational efficiency, and ensure model robustness and production stability
• Own the training and application of LLMs and MLLMs for content safety use cases, including post-training techniques such as SFT, RLHF, DPO, and safety alignment
• Drive the exploration and productionization of emerging capabilities such as AI Agents, multimodal reasoning, and video understanding to build next-generation intelligent moderation systems

Qualifications

Minimum Qualifications:

• Bachelor degree or above in Computer Science, Software Engineering, Artificial Intelligence, Mathematics, or related fields
• Strong understanding of machine learning and deep learning, with familiarity with Transformer architectures, LLMs, and MLLMs
• Hands-on experience in Python, PyTorch, distributed training, and large-scale data processing, with solid algorithmic and engineering capabilities
• Proven ability to solve complex problems and collaborate effectively in cross-functional teams, with a track record of driving projects to high-quality execution

Preferred Qualifications:

• Hands-on experience with LLM post-training, multimodal understanding, AI Agents, or Trust & Safety systems is desirable
• Publications in academic conferences such as NeurIPS, ICML, ICLR, CVPR, ECCV, ICCV, ACL, EMNLP, NAACL, Interspeech, ICASSP, and others are a strong plus