The opportunity
The Discovery team at Anthropic is organized around the north star goal of building an AI scientist – a system capable of solving the long-term reasoning challenges and basic capabilities necessary to push the scientific and technological frontier.
What you'll do
Design, build, and study reinforcement learning environments, rewards, and: training data that improve Claude's capabilities in engineering and the applied sciences
Create benchmarks and evaluation frameworks that measure model performance on: realistic engineering and scientific workflows
Develop simulation-based training environments and verifiers, working with: domain experts to validate them against real-world data
Develop approaches to long-horizon task completion, multi-agent: collaboration, and complex reasoning essential for real engineering and research work
Research how models can learn efficiently from experiments and real-world feedback
Study how environments and rewards behave in large-scale training, including: robustness, calibration, and generalization, so that training produces models that are both capable and well aligned
What they're looking for
- Experience with reinforcement learning and pre-training on large language: models, including environment and reward design
- Familiarity with large-scale language model training, evaluation, and inference pipelines
- Published research or practical experience in AI for science or engineering, or in long-horizon reasoning
- A degree or work experience in an engineering or applied science discipline,: such as mechanical, electrical, materials, chemical, aerospace, systems, or manufacturing engineering, applied physics, or computational simulation
- Experience building simulators, surrogate models, or simulation-based: environments and verifiers, and calibrating and validating them against real-world data
- Experience with large-scale data pipelines and technical or multimodal datasets
- Demonstrated ability to work across multiple domains, such as language: modeling, systems engineering, and scientific computing
