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Senior ML Engineer — autonomous driving
XPeng
Cette annonce est pensée pour les profils IA : compétences et outils clairs pour savoir si le poste correspond avant de postuler — et pour réduire les mauvais matchs au screening.
4 compétences 2 outils
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Lieu de travail Hybrid
Localisation 15 KaiDa Er Lu, Huangpu, Guangzhou 510530, China · Hybrid
Rémunération CNY 400k–650k/year + equity Niveau d’expérience Avantages Equity, hybrid Huangpu, EV perks. Comment postuler Perception, planning ML, or simulation with on-road metrics.
Publiée le 15 déc. 2026 XPeng is hiring a Senior Senior ML Engineer — autonomous driving on the XPILOT perception team (Hybrid · Guangzhou, China). This is a hands-on role in computer vision & geospatial AI —not a generic “AI enthusiast” post.
You will own vision, sensor, or geospatial models in production 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.
XPeng is a leading Chinese smart EV maker — XPILOT autonomous driving and in-cabin AI from Guangzhou Huangpu .
Senior ML Engineer (hybrid Guangzhou): perception , prediction , and simulation ML for production ADAS stacks.
About XPeng
NYSE-listed EV innovator with R&D center in Guangzhou. Fleet data from millions of kilometers drives model iteration. Tight integration between cloud training and edge Orin deploys. What you will do
Train vision transformers on multi-camera fused datasets. Close sim-to-real gaps with synthetic data pipelines. Meet automotive functional-safety collaboration requirements. Stack & environment
Python, PyTorch, CUDA, C++, internal sim platform. Hybrid Huangpu; Mandarin required. What we look for
5+ years CV/ML in automotive or robotics. 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.
Computer Vision
Image or video models with clear eval harnesses (precision/recall, calibration, or domain-specific scores).
C++
Practical C++ experience applied to vision, sensor, or geospatial models in production in production or rigorous pilots.
CUDA Tool
Regular use of CUDA in the computer vision & geospatial AI stack—configuration, debugging, and team conventions.
Docker Tool
Containerized services and reproducible dev environments for ML and LLM workloads.
✓ You can show evidence in your application: Perception, planning ML, or simulation with on-road metrics. ✓ Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, Computer Vision, C++, and CUDA. ✓ You have owned vision, sensor, or geospatial models in production in production: debugging live issues, running postmortems, and iterating from real user or business signals. ✓ You are comfortable with the hybrid rhythm (Hybrid · Guangzhou, 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 400k–650k/year + equity, benefits in At a glance) and your expectations align. Ce que l’employeur demande
Perception, planning ML, or simulation with on-road metrics.
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Intitulé
Senior ML Engineer — autonomous driving
Postuler Pensé pour les équipes qui recrutent des personnes qui travaillent avec l’IA, pas seulement autour.
Les candidats voient compétences et outils dès le départ ; vous recevez des candidatures structurées dans un seul tableau de bord.
Touchez les praticiens IA qui parcourent les offres avec des attentes « preuve d’abord ».
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