The company is looking to develop sophisticated techniques for teaching AI systems to understand and embody human values, as well as to push forward AI capabilities.
Requirements
- Strong engineering background in machine learning, with demonstrable expertise in preference learning, reinforcement learning, deep learning, or related areas
- Proficient in Python, deep learning frameworks, and distributed computing
- Familiar with modern LLM architectures and alignment techniques
- Experience with improving model training pipelines and building data pipelines
- Proficiency in Python and experience with deep learning frameworks is required for this role
- Experience with reward models is not required, but experience with LLMs or other large models is a significant plus
Responsibilities
- Help implement novel reward modeling architectures and techniques
- Optimize training pipelines
- Build and optimize data pipelines
- Collaborate across teams to integrate reward modeling advances into production systems
- Communicate engineering progress through internal documentation and potential publications
Other
- At least a Bachelor's degree in a related field or equivalent experience
- Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time
- Visa sponsorship: We do sponsor visas, but we aren't able to successfully sponsor visas for every role and every candidate
- Clear communication of complex technical concepts and research findings
- Deep interest in AI alignment and safety
- Strong communication skills
