AI role · Open offer
Senior ML Engineer — autonomous driving
XPeng
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
- 15 KaiDa Er Lu, Huangpu, Guangzhou 510530, China · Hybrid
- Compensation
- CNY 400k–650k/year + equity
- Experience level
- Senior
- Team
- XPILOT perception
- Benefits & perks
About this role
What the team is looking for and how this position fits.
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.
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.
- Computer Vision
Tools & stack
Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).
- CUDATool
Regular use of CUDA in the computer vision & geospatial AI stack—configuration, debugging, and team conventions.
- DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.
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: 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.
- ✓
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What the employer asked for
Perception, planning ML, or simulation with on-road metrics.
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