Job description
You will build systems that transform pre-trained models into aligned and general agents. You will develop data-generation pipelines, reward models, reinforcement-learning algorithms, and inference-time scaling techniques, while collaborating across pre-training and post-training work to improve model capabilities.
Responsibilities
- Build systems that transform pre-trained models into aligned and general agents.
- Drive post-training research and engineering initiatives.
- Develop data-generation pipelines, reward models, reinforcement-learning algorithms, and inference-time scaling techniques.
- Collaborate across pre-training and post-training work to improve model capability.
- Advance understanding of model reasoning, instruction following, and reinforcement learning.
Requirements
- Machine learning fundamentals and practical experience with large-scale LLM training.
- Engineering skills in complex machine-learning codebases and distributed systems.
- Experience improving model behavior through data, reward modeling, or reinforcement-learning techniques.
- Experience owning research or engineering agendas that produced measurable model improvements.
- Ability to work across research and infrastructure boundaries.
- Communication and collaborative working skills.
Benefits
- Stock options.
- Comprehensive medical, dental, vision, and life insurance.
- Annual wellness allowance.
- Daily in-office lunch and dinner.
- 22 weeks of paid parental leave.
- Unlimited paid time off in the U.S. and 30 days in the U.K.
- Visa sponsorship and long-term immigration-pathway support where applicable.
- Regular off-sites, happy hours, and team celebrations.
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