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Senior ML Engineer — recommendation & LLM
ByteDance
Este anuncio está pensado para talento nativo en IA : habilidades y herramientas claras para saber si encajas antes de aplicar — y para reducir descartes por desajuste.
4 habilidades 2 herramientas
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Modalidad Hybrid
Ubicación Zhichun Road, Haidian District, Beijing 100086, China · Hybrid
Compensación CNY 450k–750k/year + bonus Nivel de experiencia Beneficios On-campus perks, hybrid Haidian, annual bonus. Cómo aplicar Feed ranking, multimodal content understanding, or LLM features.
Publicada 27 nov 2026 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. 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.
Kubernetes Tool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
Spark Tool
Distributed feature generation and batch scoring on large tabular or event datasets.
✓ 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. Lo que pide la empresa
Feed ranking, multimodal content understanding, or LLM features.
Inicia sesión con cuenta candidato para aplicar
Regístrate, añade titular y bio; luego podrás adjuntar enlace o PDF de CV en Mi cuenta antes de aplicar. Así las candidaturas quedan ligadas a tu perfil.
Sugerencias
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Título
Senior ML Engineer — recommendation & LLM
Aplicar Pensado para equipos que contratan personas que trabajan con IA, no solo alrededor.
Los candidatos ven habilidades y herramientas al inicio; recibes candidaturas estructuradas en un solo panel.
Llega a profesionales de IA que buscan roles con expectativas basadas en pruebas.
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