Hardcore Engineer - Multimodal Infrastructure
Job Description
- Strong engineering skills with passion to improve different aspects of data and model.
- Has worked on one or more modalities other than text for model training/serving optimization.
- Keeping up with state-of-the-art techniques for preparing multimodal training data.
- Design, build, and implement large-scale distributed training systems.
- Profiling, debugging, and optimizing GPU utilization for multimodal model training and inference.
- Building scalable infrastructure for multimodal data management and crawling.
- Hardware / Software / Algorithm co-design.
- Equity
- Comprehensive medical, vision, and dental coverage
- Access to a 401(k) retirement plan
- Short & long-term disability insurance
- Life insurance
- Various other discounts and perks
About xAI
xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All engineers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
About the Role
The omni team at xAI creates magical AI experiences beyond text, enabling understanding and generation of content across various modalities, including image, video, and audio.
As a software infrastructure engineer on multimodal, you will develop and optimize scalable frameworks and software for large-scale machine-learning tasks, including model training, inference, and large-scale data processing. You will work together with other members in the omni team and the product team to push the frontiers of model capability as well as the end-to-end user experience.
Focus
- Design, build, and implement large-scale distributed training systems.
- Profiling, debugging, and optimizing GPU utilization for multimodal model training and inference.
- Building scalable infrastructure for multimodal data management and crawling.
- Hardware / Software / Algorithm co-design.
Ideal Experiences
- Strong engineering skills with passion to improve different aspects of data and model.
- Has worked on one or more modalities other than text for model training/serving optimization.
- Keeping up with state-of-the-art techniques for preparing multimodal training data.
Location
The role is based in the Bay Area [Palo Alto and San Francisco]. Candidates are expected to be located near the Bay Area or open to relocation.
Tech Stack
- Python
- Jax / PyTorch
- Spark / Ray
- Rust
Interview Process
After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 15 minute interview (“phone interview”) during which a member of our team will ask some basic questions. If you clear the initial phone interview, you will enter the main process, which consists of four technical interviews:
- One-on-one engineering discussion & coding interviews (three meetings total)
- Project deep-dive: Present your past exceptional work and your vision with xAI to a small audience.
Every application is reviewed by a member of our technical team. All interviews will be conducted via Google Meet.
Annual Salary Range
$180,000 - $440,000 USD
Benefits
Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
xAI is an equal opportunity employer.
