2 days ago

Machine Learning Engineer, Monetization Data Alignment

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Build scalable machine learning systems that power TikTok monetization by improving AI labeling, content understanding, and data quality. Work across research and production to develop multimodal (text, image, audio, video, live) models, labeling automation, taxonomy/tag generation, rule retrieval, and risk detection. Apply LLM/MLLM, NLP, CV, and multimodal learning, and productionize agentic and reinforcement learning workflows with interpretable, traceable decision logic.

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and develop ML solutions for AI labeling and content understanding for TikTok monetization use cases across ads and short video.
•Apply and improve LLM/MLLM, NLP, CV, and multimodal learning to enhance fine-grained understanding of text, image, audio, video, and live content.
•Build systems for labeling automation, intent recognition, taxonomy/tag generation, rule retrieval, risk detection, and quality evaluation to improve accuracy and efficiency.
•Explore and productionize agent and reinforcement learning approaches for complex, multi-step decision-making with tool use and adaptive content analysis.
•Develop interpretable, traceable solutions (e.g., CoT-style reasoning and explanation generation) to improve trustworthiness and usability of model outputs.

Key Requirements

•Bachelor’s degree or above in Computer Science, Artificial Intelligence, Mathematics, Statistics, or a related field.
•3+ years of experience in machine learning/applied AI or related algorithm engineering, taking models from experimentation to production.
•Strong foundation in ML/deep learning with experience in one or more: LLM/MLLM, NLP, CV, multimodal learning, representation learning, or intelligent agents.
•Hands-on experience with large model training, fine-tuning, evaluation, inference, or deployment, including methods such as prompting, supervised fine-tuning, retrieval augmented generation, chain-of-thought reasoning, or model alignment.
•Ability to solve ambiguous business problems with practical ML designs and collaborate with cross-functional stakeholders in a fast-paced environment.

Experience:3+ yearsAdsE-commerceLive streamingMultimodal AIAI labeling

Education:Bachelor's

Skills:CollaborationCommunicationProblem-solving

Languages:English

Tech Stack:LLMMLLMNLPCVMultimodal learningRepresentation learningIntelligent agentsReinforcement learningRLHFRLAIFRetrieval augmented generationChain-of-thoughtModel alignmentMultimodal large modelsAgent workflowsTaxonomy/tag generationRule retrieval

Company Brief

TikTok

Short-form video platform that lets users create, share, and discover entertainment content through algorithmic recommendations. It also offers advertising and creator tools for brands, influencers, and businesses.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn

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TikTok

2 days ago

Machine Learning Engineer, Monetization Data Alignment

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Design and develop ML solutions for AI labeling and content understanding for TikTok monetization use cases across ads and short video.
•Apply and improve LLM/MLLM, NLP, CV, and multimodal learning to enhance fine-grained understanding of text, image, audio, video, and live content.
•Build systems for labeling automation, intent recognition, taxonomy/tag generation, rule retrieval, risk detection, and quality evaluation to improve accuracy and efficiency.
•Explore and productionize agent and reinforcement learning approaches for complex, multi-step decision-making with tool use and adaptive content analysis.
•Develop interpretable, traceable solutions (e.g., CoT-style reasoning and explanation generation) to improve trustworthiness and usability of model outputs.

Key Requirements

•Bachelor’s degree or above in Computer Science, Artificial Intelligence, Mathematics, Statistics, or a related field.
•3+ years of experience in machine learning/applied AI or related algorithm engineering, taking models from experimentation to production.
•Strong foundation in ML/deep learning with experience in one or more: LLM/MLLM, NLP, CV, multimodal learning, representation learning, or intelligent agents.
•Hands-on experience with large model training, fine-tuning, evaluation, inference, or deployment, including methods such as prompting, supervised fine-tuning, retrieval augmented generation, chain-of-thought reasoning, or model alignment.
•Ability to solve ambiguous business problems with practical ML designs and collaborate with cross-functional stakeholders in a fast-paced environment.

Experience:3+ yearsAdsE-commerceLive streamingMultimodal AIAI labeling

Education:Bachelor's

Skills:CollaborationCommunicationProblem-solving

Languages:English

Company Brief

TikTok

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn