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Senior ML Engineer — TikTok ML | ByteDance | Beijing · Ganloss

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AI role · Open offer

Senior ML Engineer — recommendation & LLM

ByteDance

Full-time
Senior
Douyin & TikTok ML
Hybrid
Zhichun Road, Haidian District, Beijing 100086, China · Hybrid
Beijing, China
CNY 450k–750k/year + bonus

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

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At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Hybrid
Location: Zhichun Road, Haidian District, Beijing 100086, China · Hybrid
Compensation: CNY 450k–750k/year + bonus
Experience level: Senior
Team: Douyin & TikTok ML
Benefits & perks: On-campus perks, hybrid Haidian, annual bonus.
How to apply: Feed ranking, multimodal content understanding, or LLM features.
Company site: www.bytedance.com
Listed: Jun 7, 2026
Updated: Aug 3, 2026

About this role

What the team is looking for and how this position fits.

ByteDance is hiring a Senior Senior ML Engineer — recommendation & LLM on the Douyin & TikTok ML team (Hybrid · Beijing, China). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

ByteDance builds TikTok, Douyin, and global content platforms — recommendation and generative AI at billion-user scale from Beijing Haidian.

Senior ML Engineer (hybrid Beijing): feed ranking, multimodal understanding, and LLM features with strict latency budgets.

About ByteDance

Global technology company; Haidian R&D center for core ML systems.
Real-time recommendation infra handles massive QPS.
Mandarin-primary teams with international research reading.

What you will do

Improve ranking models with causal and long-term engagement metrics.
Build multimodal embeddings for video and text content.
Prototype LLM assistants with content-safety filters.

Stack & environment

Python, PyTorch, Spark, Kubernetes.
Hybrid Beijing Haidian.

What we look for

Large-scale recommender or NLP systems.
Eligible to work in China; Mandarin proficiency.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
SQL
Analytical SQL for features, cohorts, label quality, and experiment analysis at scale.
NLP
Text pipelines: tokenization, fine-tuning, evaluation, and guardrails for user-facing language features.

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

KubernetesTool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
SparkTool
Distributed feature generation and batch scoring on large tabular or event datasets.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Feed ranking, multimodal content understanding, or LLM features.
Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, NLP, and Kubernetes.
You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · Beijing, China)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: CNY 450k–750k/year + bonus, benefits in At a glance) and your expectations align.

Apply

Candidate accounts only: add your headline and bio on My account, and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Feed ranking, multimodal content understanding, or LLM features.

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Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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