Machine Learning Engineer - Foundation Model

Up Closets of North Cincinnati; Santa Clara (CA); On-site; USD 148,000 - 252,000; Full time

Job summary

An innovative company is seeking a passionate Machine Learning Engineer to join their team and contribute to the future of autonomous driving. In this exciting role, you will design and deploy large-scale deep learning models, leveraging extensive data from a fleet of vehicles. Collaborating with top talents, you will push the boundaries of machine learning and make a significant impact in reshaping transportation. With a supportive and engaging environment, this opportunity offers competitive compensation and the chance to work with cutting-edge technologies that redefine mobility. If you're enthusiastic about AI and eager to tackle complex challenges, this role is perfect for you.

Benefits

Supportive work environment

Infrastructures and computational resources

Opportunity to work on cutting-edge technologies

Competitive compensation package

Snacks, lunches, dinners, and fun activities

Qualifications

• Master's degree in CS/CE/EE or equivalent with 1-3 years of experience.
• Strong knowledge of PyTorch and distributed training.

Responsibilities

• Design, train, and deploy large deep learning models using vast data.
• Collaborate with engineers to innovate autonomous driving solutions.

Skills

PyTorch

Machine Learning

Transformer Architecture

Distributed Training (PyTorch DDP)

Problem Solving

Education

Master in Computer Science

Master in Computer Engineering

Master in Electrical Engineering

Tools

PyTorch Lightning

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 models 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:

1. Master in CS/CE/EE, or equivalent, with 1-3 years of industry experience.
2. Good knowledge of PyTorch.
3. Knowledge of model training framework (e.g. PyTorch Lightning).
4. Knowledge of transformer architecture and ways to accelerate the training and inference of transformer models.
5. Experience of using PyTorch DDP for distributed training of models.

Preferred Skill Requirements:

1. Strong publications records in top academic conferences or journals, e.g. CVPR, NeurIPS, ICML, ICCV, ECCV, ICLR.
2. Experience in training large scale vision or language models.
3. Previous experience in the autonomous driving industry.
4. Being efficient in 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 advancing autonomous driving.
5. Competitive compensation package.
6. Snacks, lunches, dinners, and fun activities.

The base salary range for this full-time position is $148,909 - $252,000, 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.