Anthropic Limited
Research Scientist / Research Engineer, Pretraining
Anthropic Limited, San Francisco, California, United States, 94199
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 Scientist / Research Engineer to join our Pretraining 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.
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
You'll thrive in this role if you:
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
Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects
Are 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
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
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.
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!
#J-18808-Ljbffr
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
You'll thrive in this role if you:
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
Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects
Are 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
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
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.
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!
#J-18808-Ljbffr