Senior Staff AI Performance Engineer

Up Closets of North Cincinnati; Santa Clara (CA); On-site; USD 244,000 - 414,000; Full time

Job summary

Join a forward-thinking company as a full-time AI Performance Engineer, where you'll optimize cutting-edge machine learning models for autonomous driving. Collaborate with top talents to push the boundaries of technology and make a significant impact in transforming the future of transportation. This role offers a dynamic and supportive environment, where your contributions will shape the next generation of smart vehicles. With competitive compensation and a focus on innovation, this is an exciting opportunity for those passionate about AI and autonomous systems.

Benefits

Supportive work environment

Cutting-edge technologies

Competitive compensation package

Snacks and meals provided

Fun activities

Qualifications

• PhD in relevant field or equivalent industry experience required.
• 4+ years experience with C++ and Python programming.

Responsibilities

• Optimize performance of Deep Learning training workloads on NVIDIA GPUs.
• Reduce latency of model inference on autonomous vehicle systems.

Skills

C++ Programming

Python Programming

Deep Learning Optimization

Parallel Programming

Workload Analysis

Education

PhD in Computer Science/Computer Engineering/Electrical Engineering

Tools

NVIDIA GPU Systems

PyTorch

Job description

XPeng Motors is one of China’s leading smart electric vehicle (“EV”) companies. We design, develop, manufacture and market smart EVs that are seamlessly integrated with advanced Internet, AI and autonomous driving technologies. We are committed to in-house R&D and intelligent manufacturing to create a better mobility experience for our customers. We strive to transform smart electric vehicles with technology and data, shaping the mobility experience of the future.

We are looking for a full-time AI Performance Engineer, with deep knowledge and strong enthusiasm towards optimizing the training and inference performance of state-of-art ML infrastructure and foundation models for autonomous driving.

Our mission is to solve the autonomous driving problem. You will work with a team of talented software engineers, machine learning engineers and research scientists to push the boundary of state-of-art machine learning models which will enable the next-generation E2E solution of autonomous driving.

Job Responsibilities:

1. Optimize the performance of Deep Learning training workload on NVIDIA GPU systems on a large scale.
2. Optimize the latency of model inference and model pre- and post-processing on AV onboard systems.

Minimum Skill Requirements:

1. PhD in CS/CE/EE, or equivalent, in industry experience.
2. 4+ years of experience with C++ and Python programming.
3. Knowledge of Computer Architecture and Operating Systems.
4. Background with parallel programming, preferably on GPUs.
5. Capability to analyze/profile workloads and do detective work to reduce system latency.
6. A track record of delivery CPU or GPU latency optimization for real-world engineering systems.

Preferred Skill Requirements:

1. Previous experience in the autonomous driving industry.
2. Experience in PyTorch.
3. Proven experience developing large software projects with engineering excellence.
4. A track record of efficiently solving complex problems collaboratively on larger teams.

What do we provide:

1. A fun, supportive and engaging environment.
2. Infrastructures and computational resources to support your work.
3. Opportunity to work on cutting edge technologies with the top talents in the field.
4. Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.
5. Competitive compensation package.
6. 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.