LLM & Agent Algorithm Expert - TikTok Search

TikTok
Singapore
Workplace: OnsiteFull timeFunction: Administration & Executive AssistanceEducation: bachelorsSkills: ["Technical leadership","Cross-team collaboration","Communication","Research ownership","Engineering judgment"]

Build and iterate the search-domain LLM foundation and agent execution framework that powers TikTok Search’s shift from retrieval to proactive, long-horizon task agents. Lead the training–inference–evaluation loop with long-term memory, self-improvement (RSI), and reward/verifier systems. Develop high-quality vertical data synthesis and multimodal capabilities (image/video, visual search, OCR, TinyLLM), while exploring next-gen architectures and safety/alignment for large multi-agent systems.

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FursaFursa
TikTok
TikTok
1 month ago

LLM & Agent Algorithm Expert - TikTok Search

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Last checked: 20 hours agoStatus: Live

Job Summary

Build and iterate the search-domain LLM foundation and agent execution framework that powers TikTok Search’s shift from retrieval to proactive, long-horizon task agents. Lead the training–inference–evaluation loop with long-term memory, self-improvement (RSI), and reward/verifier systems. Develop high-quality vertical data synthesis and multimodal capabilities (image/video, visual search, OCR, TinyLLM), while exploring next-gen architectures and safety/alignment for large multi-agent systems.
Location: Singapore
Workplace: Onsite
Employment Type: Full time
Job Function: Administration & Executive Assistance

Key Responsibilities

  • •Lead R&D and iteration of the search-domain LLM foundation, including pre-training/post-training pipelines and inference optimization for long context and efficiency.
  • •Own the 0→1/1→N build-out of the agent execution framework (Harness), including orchestration of tool calling, planning, memory, environment interaction, and multi-agent collaboration/scheduling.
  • •Drive the agent loop and training–inference–evaluation closed loop by building long-term memory, causal reasoning, and recursive self-improvement (RSI) mechanisms.
  • •Build vertical-domain data synthesis and quality control, and develop online reward/verifier and benchmark evaluation for long-cycle, cross-domain tasks.
  • •Support business scaling by enabling long-horizon task agents and multimodal experiences (multimodal AIGC, visual search, on-device intelligence via object detection/OCR/TinyLLM).

Key Requirements

  • •Bachelor’s degree or above in Computer Science (or related) with AI algorithm R&D experience.
  • •Hands-on research and implementation experience in LLM/agent/multimodal/search, able to independently own and lead a technical direction.
  • •Strong mastery of an LLM/agent stack, including full-pipeline LLM (pre-training/SFT/RLHF/alignment/inference optimization/data synthesis) and/or full-stack agent systems (Harness, multi-agent scheduling, memory, agent loop, RSI, reward/verifier).
  • •Strong engineering for distributed training, mixed-precision training, and inference acceleration (quantization/pruning/distillation/TensorRT) plus large-scale data processing (e.g., MapReduce/Spark).
  • •Demonstrated familiarity with CV & multimodal and/or NLP foundations (e.g., retrieval/recognition, segmentation, object detection, OCR, multilingual learning, NLG).
Experience:AILLMAI agentsMultimodalSearchComputer visionNLP
Education:Bachelor's
Skills:Technical leadershipCross-team collaborationCommunicationResearch ownershipEngineering judgment
Tech Stack:LLMAgentsHarnessMulti-agent schedulingTool callingPlanningMemory mechanismsAgent LoopSelf-improvement (RSI)Reward/VerifierQuantizationPruningDistillationInference accelerationTensorRTMapReduceSparkSFTRLHFAlignment

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
WebsiteLinkedIn