Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests.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. You'll thrive in this role if you're enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects. You're working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research. You view research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximize the impact of your insights. You have ambitious goals for AI safety and general progress in the next few years, and you're working to create the best outcomes over the long-term.
Key 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 Qualifications: 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 Preferred Experience: 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 Strong Candidates May Also: Have significant software engineering experience Are results-oriented with a bias towards flexibility and impact Willingly take on tasks outside your job description to support the team Enjoy pair programming and collaborative work Are eager to learn more about machine learning research Sample Projects: Optimizing the throughput of novel attention mechanisms Comparing compute efficiency of different Transformer variants Preparing large-scale datasets for efficient model consumption Scaling distributed training jobs to thousands of GPUs Designing fault tolerance strategies for our training infrastructure Creating interactive visualizations of model internals, such as attention patterns At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.
If you're excited about pushing the boundaries of AI while prioritizing safety and ethics, we want to hear from you!
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