Senior Machine Learning Engineer - TikTok Short Video Content Understanding/Multimodal Recommendation
Sep 24, 2025 San Jose
About us
TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
- Size: 5,001 - 10,000 employees
- Industry: Entertainment & Gaming
Responsibilities
Our team's mission is to empower content understanding for TikTok Short Video business. We focus on cutting-edge research in content understanding and the development of advanced LLM/MLLM algorithms and applications, including generative recommendation, weakly-supervised learning, few-shot classification, video tagging, multi-task learning, multilingual learning, multimodal pretraining, and more. We aim to succeed both in driving measurable business impact (e.g., recommendation metrics) and delivering state-of-the-art research outputs.
Responsibilities
1. Lead multimodal algorithm development for TikTok's short-video business, explore applications of multimodal technologies in recommendation systems and other scenarios to improve key business metrics.
2. Conduct cutting-edge research in multimodal and MLLM technologies, design advanced algorithms to solve business requirements while achieving technical breakthroughs.
3. Drive engineering deployment and implementation, ensuring model stability, scalability, and efficiency in production environments.
4. Focus on key areas including (but not limited to):
- General AI platform design and development, including few-shot/zero-shot on MLLM, AI-labeling, auto prompting, active-learning, continue pretraining and RL.
- Integration of content understanding with recommendation systems (e.g., UGC ecosystems, cold start, interest exploration, comment understanding).
- Leveraging multimodal techniques to develop next-generation recommendation systems, such as generative models and end-to-end approaches.
Qualifications
Minimum Qualifications
1. Proven experience in multimodal content understanding, with expertise in large language models (LLMs) and familiarity with cutting-edge progress in the field.
2. Strong technical foundation in at least one major deep learning framework (e.g., PyTorch, TensorFlow).
3. Proactive mindset, strong sense of ownership, excellent communication skills, and ability to collaborate across teams.
Preferred Qualification
1. Hands-on experience deploying content understanding solutions in search, advertising, recommendation, or related domains.
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.
Our team's mission is to empower content understanding for TikTok Short Video business. We focus on cutting-edge research in content understanding and the development of advanced LLM/MLLM algorithms and applications, including generative recommendation, weakly-supervised learning, few-shot classification, video tagging, multi-task learning, multilingual learning, multimodal pretraining, and more. We aim to succeed both in driving measurable business impact (e.g., recommendation metrics) and delivering state-of-the-art research outputs.
Responsibilities
1. Lead multimodal algorithm development for TikTok's short-video business, explore applications of multimodal technologies in recommendation systems and other scenarios to improve key business metrics.
2. Conduct cutting-edge research in multimodal and MLLM technologies, design advanced algorithms to solve business requirements while achieving technical breakthroughs.
3. Drive engineering deployment and implementation, ensuring model stability, scalability, and efficiency in production environments.
4. Focus on key areas including (but not limited to):
- General AI platform design and development, including few-shot/zero-shot on MLLM, AI-labeling, auto prompting, active-learning, continue pretraining and RL.
- Integration of content understanding with recommendation systems (e.g., UGC ecosystems, cold start, interest exploration, comment understanding).
- Leveraging multimodal techniques to develop next-generation recommendation systems, such as generative models and end-to-end approaches.
Minimum Qualifications
1. Proven experience in multimodal content understanding, with expertise in large language models (LLMs) and familiarity with cutting-edge progress in the field.
2. Strong technical foundation in at least one major deep learning framework (e.g., PyTorch, TensorFlow).
3. Proactive mindset, strong sense of ownership, excellent communication skills, and ability to collaborate across teams.
Preferred Qualification
1. Hands-on experience deploying content understanding solutions in search, advertising, recommendation, or related domains.
Our team's mission is to empower content understanding for TikTok Short Video business. We focus on cutting-edge research in content understanding and the development of advanced LLM/MLLM algorithms and applications, including generative recommendation, weakly-supervised learning, few-shot classification, video tagging, multi-task learning, multilingual learning, multimodal pretraining, and more. We aim to succeed both in driving measurable business impact (e.g., recommendation metrics) and delivering state-of-the-art research outputs.
Responsibilities
1. Lead multimodal algorithm development for TikTok's short-video business, explore applications of multimodal technologies in recommendation systems and other scenarios to improve key business metrics.
2. Conduct cutting-edge research in multimodal and MLLM technologies, design advanced algorithms to solve business requirements while achieving technical breakthroughs.
3. Drive engineering deployment and implementation, ensuring model stability, scalability, and efficiency in production environments.
4. Focus on key areas including (but not limited to):
- General AI platform design and development, including few-shot/zero-shot on MLLM, AI-labeling, auto prompting, active-learning, continue pretraining and RL.
- Integration of content understanding with recommendation systems (e.g., UGC ecosystems, cold start, interest exploration, comment understanding).
- Leveraging multimodal techniques to develop next-generation recommendation systems, such as generative models and end-to-end approaches.
Qualifications
Minimum Qualifications
1. Proven experience in multimodal content understanding, with expertise in large language models (LLMs) and familiarity with cutting-edge progress in the field.
2. Strong technical foundation in at least one major deep learning framework (e.g., PyTorch, TensorFlow).
3. Proactive mindset, strong sense of ownership, excellent communication skills, and ability to collaborate across teams.
Preferred Qualification
1. Hands-on experience deploying content understanding solutions in search, advertising, recommendation, or related domains.
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
ResponsibilitiesOur team's mission is to empower content understanding for TikTok Short Video business. We focus on cutting-edge research in content understanding and the development of advanced LLM/MLLM algorithms and applications, including generative recommendation, weakly-supervised learning, few-shot classification, video tagging, multi-task learning, multilingual learning, multimodal pretraining, and more. We aim to succeed both in driving measurable business impact (e.g., recommendation metrics) and delivering state-of-the-art research outputs.
Responsibilities
1. Lead multimodal algorithm development for TikTok's short-video business, explore applications of multimodal technologies in recommendation systems and other scenarios to improve key business metrics.
2. Conduct cutting-edge research in multimodal and MLLM technologies, design advanced algorithms to solve business requirements while achieving technical breakthroughs.
3. Drive engineering deployment and implementation, ensuring model stability, scalability, and efficiency in production environments.
4. Focus on key areas including (but not limited to):
- General AI platform design and development, including few-shot/zero-shot on MLLM, AI-labeling, auto prompting, active-learning, continue pretraining and RL.
- Integration of content understanding with recommendation systems (e.g., UGC ecosystems, cold start, interest exploration, comment understanding).
- Leveraging multimodal techniques to develop next-generation recommendation systems, such as generative models and end-to-end approaches.
Qualifications
QualificationsMinimum Qualifications
1. Proven experience in multimodal content understanding, with expertise in large language models (LLMs) and familiarity with cutting-edge progress in the field.
2. Strong technical foundation in at least one major deep learning framework (e.g., PyTorch, TensorFlow).
3. Proactive mindset, strong sense of ownership, excellent communication skills, and ability to collaborate across teams.
Preferred Qualification
1. Hands-on experience deploying content understanding solutions in search, advertising, recommendation, or related domains.
Additional Information
- Salary: $162,000 – $387,600
- Posted: Sep 24, 2025