ML Engineer — Content Ecology & AI Platforms

TikTok; San Jose (CA); On-site; USD 128,000 - 317,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with company match

Paid parental leave

Disability coverage

Wellbeing benefits

Job summary

TikTok is hiring for an AI/ML focused role in San Jose. The Content Ecology team builds AI-powered platforms to enhance content creation, understanding, discovery, and governance, using LLMs, multimodal learning, and agentic AI to impact users, creators, and merchants.

The candidate will work on scalable AI infrastructure, model and agent lifecycles, and cutting-edge systems like planning, tool use, and memory. A PhD and strong ML framework experience are highly valued.

Qualifications

• PhD completed or near completion in CS/EE/Math or related field.
• Strong programming and algorithmic skills in Python or C++.
• Deep understanding of NLP, CV, LLM/MLLM, Search, or Agentic AI.

Responsibilities

• Architect and build standardized, configurable, and reusable pipelines for the entire lifecycle of models and agents—from data processing and training to deployment, monitoring, and governance.
• Partner with algorithm teams to understand their needs and provide an infrastructure platform that accelerates R&D cycles.
• Build robust observability and evaluation frameworks to ensure reproducibility, reliability, and cost-efficiency of AI workloads at scale.
• Design and implement core platform infrastructure, including model/agent registries, feature stores, and high-throughput retrieval/RAG systems.
• Design, build, and optimize advanced Agentic AI systems, focusing on planning, tool use, and memory.

Skills

Python

C++

NLP/LLM/Agentic AI

TensorFlow/PyTorch

Communication skills

Education

PhD in computer science or related

Tools

TensorFlow

PyTorch

Job description

TikTok is hiring for an AI/ML focused role in San Jose. The Content Ecology team builds AI-powered platforms to enhance content creation, understanding, discovery, and governance, using LLMs, multimodal learning, and agentic AI to impact users, creators, and merchants.

The candidate will work on scalable AI infrastructure, model and agent lifecycles, and cutting-edge systems like planning, tool use, and memory. A PhD and strong ML framework experience are highly valued.