Senior Staff Machine Learning Compiler Engineer

The Senior Staff Machine Learning Compiler Engineer at XPENG primarily focuses on developing machine learning compilers that enable efficient execution of advanced self-driving models. Key responsibilities include Clang/MLIR/LLVM compiler toolchain development, optimizing computational graphs, and implementing backend optimizations through heterogeneous memory management and parallelization. You'll also be involved in testing and profiling deployed models to ensure optimal performance.

To qualify for the Senior Staff Machine Learning Compiler Engineer role at XPENG, candidates should possess a PhD in Computer Science, Computer Engineering, or Electrical Engineering, paired with 5-7+ years of industry experience in related fields. Strong proficiency in C/C++ development is required, alongside a solid understanding of compiler frameworks. Experience in the autonomous driving industry, familiarity with CUDA, or knowledge of GPU architectures will be advantageous.

XPENG is committed to fostering a fun and engaging work environment, providing extensive infrastructure and computational resources that support professional development. As a Senior Staff Machine Learning Compiler Engineer, you'll have opportunities to work on cutting-edge technologies alongside top industry talent, allowing you to continuously grow your skills and contribute meaningfully to advancements in autonomous driving.

As a Senior Staff Machine Learning Compiler Engineer at XPENG, you will work on projects designed to enhance the performance of machine learning models deployed in autonomous driving technologies. This includes developing compilers capable of optimizing computation on general-purpose GPUs and specialized SoC chips, and implementing innovative techniques in computational and memory optimizations that directly contribute to real-world applications in smart mobility.

The base salary range for the Senior Staff Machine Learning Compiler Engineer position at XPENG is between $244,140 and $413,160, in addition to bonuses, equity, and benefits. This range accounts for various factors such as work location, experience, and relevant education, ensuring we attract the best talent in the field.

In responding to this question, highlight specific projects where you contributed to compiler development, focusing on problems you solved and technologies you used, such as LLVM or Clang. Discuss your familiarity with back-end optimizations and front-end transformations, showcasing how your skills can directly benefit XPENG's goals.

Discuss techniques such as layer fusion, operation reordering, and pruning that you’ve employed in previous experiences. It’s important to articulate your understanding of trade-offs between computational speed and memory usage, demonstrating how these optimizations can enhance the performance of autonomous driving applications at XPENG.

Outline your methods for performance assessment, noting tools or methodologies you use, such as benchmarks or profiling tools. Discuss the importance of ensuring reliability and how you validate outputs to meet performance specifications in autonomous driving technology.

Reflect on past experiences within multi-level IR Compiler Frameworks or similar environments, and describe specific challenges like memory bottlenecks or parallel execution issues. Highlight how you overcame these challenges, which will showcase your problem-solving skills relevant to the role at XPENG.

Emphasize your commitment to continuous learning through attending conferences, reading scholarly journals, and participating in professional communities. Reference any specific trends or technologies you’re currently exploring that would benefit your work as a Senior Staff Machine Learning Compiler Engineer at XPENG.

Share examples of collaborative projects where you made significant contributions, stressing your teamwork skills, communication style, and the collaborative tools you used. This sets a tone of your ability to fit within XPENG's dynamic work environment.

Discuss your expertise in languages such as C/C++, and any specific tools like LLVM, Clang, or MLIR. Mention projects where you've effectively utilized these tools, showcasing your hands-on abilities and relevance to the Senior Staff Machine Learning Compiler Engineer position at XPENG.

Express enthusiasm for certain aspects of autonomous driving—whether it's safety systems, navigation, or machine learning models—and connect your interest to XPENG's innovative approach to intelligent mobility, illustrating how your passion aligns with the company's mission.

Cover your strategies for task prioritization, such as assessing project urgency or impact, and how you adapt your approach based on changing priorities. This demonstrates your ability to thrive in XPENG's fast-paced environment.

Provide insights drawn from industry trends and your experiences, discussing potential developments and innovations you foresee. Tie your answers back to XPENG's goals, showing you have a forward-thinking perspective.