Back to jobs
New

Senior Staff Machine Learning Performance Engineer

Santa Clara, CA
XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.
 
The Mission: We are building the next generation of end-to-end autonomous driving on physical AI foundation models — vision-language-action policies and world models — and the same training stack carries our robotics program. These training runs span thousands of accelerators and days of wall-clock — how fast we train them is how fast we learn. As a Senior Staff Machine Learning Performance Engineer, you will own that speed: working with the modeling teams on their hardest bottlenecks, setting the technical direction for performance, and turning one-off wins into defaults — including the agentic workflows that find the next round of them automatically.
 
Job Responsibilities:
  • Training Performance at Scale: Own step time, scaling efficiency and long-run stability for foundation-model training across thousands of accelerators — from the data path to kernels, parallelism and communication.
  • Cross-Team Technical Leadership: Work directly with the modeling, infrastructure, simulation, data-mining and robotics teams on their hardest bottlenecks, and set the performance direction those teams build against.
  • Reusable by Design: Turn one-off wins into modular components that become defaults across most models and workloads, rather than a patch that helps a single job.
  • Observability at Scale: Extend performance tooling and metric coverage across the stack, while keeping instrumentation overhead low enough to stay on for production jobs fleet-wide.
  • Agentic Automation: Build agents that reproduce any job on demand, verify numerical parity and separate a real regression from run-to-run noise — so that most of the optimizations that land are found and fixed by AI rather than by hand.
Minimum Skill Requirements:
  • Master's or PhD in CS, CE or EE, or equivalent practical experience, with 8+ years of industry experience, the majority of it in performance engineering.
  • Hands-on experience optimizing GPU training or inference workloads in production, at multi-node scale.
  • A track record of diagnosing performance problems in real production workloads and landing the fixes — often in systems owned by other teams — with the gain measured and verified in production.
  • In-depth understanding of computer architecture and high-performance computing.
  • Strong C++ and Python, with a solid command of data structures and algorithms.
Preferred Skill Requirements: 
  • Hands-on experience writing and tuning CUDA or Triton kernels.
  • Fluent in PyTorch, with concrete insight into what makes PyTorch code fast or slow — graph breaks, host-side overhead, synchronization points and memory layout.
  • Training at the scale of thousands of accelerators, including multi-node failure modes and long-running job stability.
  • Building profiling, tracing or benchmarking infrastructure that other teams depend on — CUPTI, Perfetto, or equivalent.
  • Using LLM agents to automate parts of an engineering workflow.
  • Autonomous driving, robotics, or another domain with hard latency, power and memory constraints.
  • Publications or open-source contributions in ML systems or performance.
What do we provide:
  • A fun, supportive and engaging environment.
  • Infrastructures and computational resources to support your work.
  • Opportunity to work on cutting edge technologies with the top talents in the field.
  • Opportunity to make a significant impact on the transportation revolution by the means of advancing autonomous driving.
  • Competitive compensation package.
  • Snacks, lunches, dinners, and fun activities.
 
The base salary range for this full-time position is $244,140, - $413,160, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
 
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

Create a Job Alert

Interested in building your career at XPENG? Get future opportunities sent straight to your email.

Apply for this job

*

indicates a required field

Resume/CV*

Accepted file types: pdf, doc, docx, txt, rtf

Cover Letter

Accepted file types: pdf, doc, docx, txt, rtf

Select...
Select...
Select...
Select...

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in XPENG’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

Select...
Select...
Race & Ethnicity Definitions

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection. As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure the effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categories is as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

A "recently separated veteran" means any veteran during the three-year period beginning on the date of such veteran's discharge or release from active duty in the U.S. military, ground, naval, or air service.

An "active duty wartime or campaign badge veteran" means a veteran who served on active duty in the U.S. military, ground, naval or air service during a war, or in a campaign or expedition for which a campaign badge has been authorized under the laws administered by the Department of Defense.

An "Armed forces service medal veteran" means a veteran who, while serving on active duty in the U.S. military, ground, naval or air service, participated in a United States military operation for which an Armed Forces service medal was awarded pursuant to Executive Order 12985.

Select...