Senior Machine Learning Engineer - Foundation Model

XPENG; Santa Clara (CA); On-site; USD 175,000 - 296,000; Full time

Benefits offered by this job

Snacks

Lunches

Dinners

Fun activities

Job summary

XPENG in Santa Clara, CA is seeking a Machine Learning Engineer to design, train, and deploy large deep learning models powering autonomous driving and AI-powered perception. You will work with a team of engineers and researchers on state-of-the-art ML infrastructure for training very large foundation models and accelerating training and inference.

The role emphasizes strong PyTorch expertise, distributed training with DDP, and experience with transformer architectures.

Qualifications

• Master's or PhD in CS/CE/EE or equivalent; open to fresh graduates.
• Strong knowledge of PyTorch and distributed training.
• Experience with transformer architectures and accelerating training/inference.

Responsibilities

• Design, train, and deploy large deep learning models that can leverage data from a fleet of vehicles.

Skills

PyTorch

PyTorch Lightning

Transformer architectures

Distributed training (DDP)

Education

Master's or PhD in CS/CE/EE

Tools

CUDA

Job description

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.

We are looking for a full-time Machine Learning Engineer, with deep knowledge and strong enthusiasm towards establishing a state-of-art ML infrastructure for training very large foundation model and accelerating model training/inference.

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:

• Design, train, and deploy large deep learning models that can leverage the vast amount of labeled and unlabeled data from a fleet of million vehicles.

Minimum Skill Requirements:

• Master in CS/CE/EE, or equivalent, with 3 + years of industry experience. Or PhD in CS/CE/EE, or equivalent. Open to fresh graduates.
• Good knowledge of PyTorch.
• Knowledge of model training framework (e.g. PyTorch Lightning)
• Knowledge of transformer architecture and ways to accelerate the training and inference of transformer models.
• Experience of using Pytorch ddp for distributed training of models.

Preferred Skill Requirements:

• Strong publications records in top academic conferences or journals, e.g. CVPR, NeurIPS, ICML, ICCV, ECCV, ICLR
• Experience in training large scale vision or language models
• Previous experience in the autonomous driving industry.
• Being efficiently in solving complex problems collaboratively on larger teams

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 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 $174,720 - $295,680, 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.