AI Engineer & Researcher - Post-training
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 and researchers are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.
About the Role
The post-training team at xAI transforms powerful pre-trained models to become steerable, versatile, and capable of understanding and addressing real-world challenges.
As a post-training researcher/engineer, you will enhance the model's instruction-following capability and general usefulness to fulfill our mission – developing AI systems that can accurately understand the universe, create new knowledge, and improve themselves through interactions.
Focus
- Creating and driving research agenda to advance model quality.
- Improving data mixtures by building data collection pipelines and developing data generation techniques.
- Creating generalizable reward models and developing novel reinforcement learning algorithms.
- Designing and implementing robust model evaluations.
- Designing and implementing large-scale model training frameworks.
- Collaborating with pre-training, reasoning, data, multimodal, applied, product efforts to push the frontiers of model capability.
Ideal Experiences
- Expert in ML and fine-tuning large language models.
- Track record in leading research that significantly impacts AI advancement.
- Experience in data-driven large language model behavior improvements.
- Experience in advanced reinforcement learning or inference-time search techniques.
- Experience in developing benchmarks or large-scale distributed machine learning systems.
- Experience in model optimizations under complex setups (e.g., multi-modality, multi-context, multi-agent, long-horizon tasks, diverse user preference/feedback).
Location
The role is based in the Bay Area [San Francisco and Palo Alto]. Candidates are expected to be located near the Bay Area or open to relocation.
Tech Stack
- Python
- Jax
- 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:
- Coding assessment in a language of your choice.
- 2 x post-training technical sessions: These sessions will be testing your ability to formulate, design and solve concrete problems in post-training. It can be research or engineering, depending on background/experience.
- Meet the Team: Present your past exceptional work and your vision with xAI to a small audience.
Our goal is to finish the main process within one week. All interviews will be conducted via Google Meet.
Annual Salary Range
$180,000 - $440,000 USD
xAI is an equal opportunity employer.
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