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JD.com
Tiempo completo Senior Retail intelligence Hybrid 20 Kechuang 11th St, Yizhuang, Beijing 101111, China · Hybrid Beijing, China CNY 420k–680k/year + bonus 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.
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Modalidad Hybrid
Ubicación 20 Kechuang 11th St, Yizhuang, Beijing 101111, China · Hybrid
Compensación CNY 420k–680k/year + bonus Nivel de experiencia Equipo Beneficios Hybrid Yizhuang, annual bonus, housing allowance. Cómo aplicar Recommendation, supply chain ML, or logistics optimization at scale.
Publicada 24 jun 2026
Actualizada 3 ago 2026 JD.com is hiring a Senior Senior ML Engineer — retail AI on the Retail intelligence team (Hybrid · Beijing, China). This is a hands-on role in search & recommendations —not a generic “AI enthusiast” post.
You will own ranking, retrieval, and online experimentation 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.
JD.com is China's largest retail and logistics technology company — autonomous warehouses, supply chain AI , and consumer recommendations from Beijing Yizhuang .
Senior ML Engineer (hybrid Beijing): personalization , inventory forecasting , and last-mile optimization at national scale.
About JD.com
Fortune Global 500 retailer with proprietary logistics network. Yizhuang HQ hosts retail AI and robotics research labs. Models serve 600M+ annual active customers. What you will do
Improve recommendation and search ranking with causal evals. Forecast demand across SKUs and regional fulfillment centers. Ship models with sub-100ms inference for mobile apps. Stack & environment
Python, PyTorch, Spark, Hive, Kubernetes. Hybrid Yizhuang; Mandarin fluency strongly preferred. What we look for
5+ years ML in e-commerce or logistics. Eligible to work in mainland China. 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.
Spark
Distributed feature generation and batch scoring on large tabular or event datasets.
Kubernetes Tool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
Hive Tool
Regular use of Hive in the search & recommendations stack—configuration, debugging, and team conventions.
✓ You can show evidence in your application: Recommendation, supply chain ML, or logistics optimization at scale. ✓ Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, Spark, and Kubernetes. ✓ You have owned ranking, retrieval, and online experimentation 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 420k–680k/year + bonus, benefits in At a glance) and your expectations align. Lo que pide la empresa
Recommendation, supply chain ML, or logistics optimization at scale.
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
Talento IA que podría interesarte Perfiles ordenados por solape con habilidades y herramientas de este rol — útil si contratas equipo o comparas candidatos.
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Título
Senior ML Engineer — retail AI
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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