Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. We are seeking a Research Engineer to join our Pre‑training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting‑edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.
Research Engineer/Research Scientist, Pre-training na Anthropic
Híbrido - San Francisco, CA, Seattle, WA, New York City, NY
Ver mais vagas na AnthropicSalary
USD 350,000 - 850,000
Requirements
Skills
- Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
- Strong software engineering skills with a proven track record of building complex systems
- Expertise in Python and experience with deep learning frameworks (PyTorch preferred)
- Familiarity with large-scale machine learning, particularly in the context of language models
- Ability to balance research goals with practical engineering constraints
- Strong problem-solving skills and a results-oriented mindset
- Excellent communication skills and ability to work in a collaborative environment
- Care about the societal impacts of your work
- Work on high-performance, large-scale ML systems
- Familiarity with GPUs, Kubernetes, and OS internals
- Experience with language modeling using transformer architectures
- Knowledge of reinforcement learning techniques
- Background in large-scale ETL processes
Responsibilities
- Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development
- Independently lead small research projects while collaborating with team members on larger initiatives
- Design, run, and analyze scientific experiments to advance our understanding of large language models
- Optimize and scale our training infrastructure to improve efficiency and reliability
- Develop and improve dev tooling to enhance team productivity
- Contribute to the entire stack, from low-level optimizations to high-level model design
Technologies
PythonPyTorchGPUKubernetesOS InternalsTransformer architecturesReinforcement LearningLarge-scale ETL
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