About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the role
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. 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 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.
Responsibilities:
- Design and implement high-performance ML training infrastructure for large language model research
- Develop and maintain core ML framework primitives in JAX, PyTorch, etc.
- Create robust automated evaluation and benchmarking systems for model performance
- Implement comprehensive monitoring and debugging tools for ML workflows
- Design and optimize data loading pipelines that maximize training throughput
- Build MLOps tooling to support reproducible research and experimentation
- Collaborate with research teams to prototype and scale novel training architectures
- Develop infrastructure for efficient hyperparameter sweeps and architecture search
You may be a good fit if you have:
- Strong software engineering skills with experience in building distributed systems
- Expertise in Python and experience with distributed computing frameworks
- Deep understanding of cloud computing platforms and distributed systems architecture
- Experience with high-throughput, fault-tolerant system design
- Strong background in performance optimization and system scaling
- Excellent problem-solving skills and attention to detail
- Strong communication skills and ability to work in a collaborative environment
Strong candidates may have:
- Advanced degree (MS or PhD) in Computer Science or related field
- Experience with language model training infrastructure
- Strong background in distributed systems and parallel computing
- Expertise in tokenization algorithms and techniques
- Experience building high-throughput, fault-tolerant systems
- Deep knowledge of monitoring and observability practices
- Experience with infrastructure-as-code and configuration management
- Background in MLOps or ML infrastructure
The expected salary range for this position is:
Annual Salary:
$315,000—$425,000 USD
Logistics
**Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
Location-based hybrid policy:** Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.