27 days ago
Base Salary
$350k - $500k/yr
Responsibilities
- Build and scale the infrastructure and data pipelines behind Safeguards machine learning research.
- Own the training, evaluation, and scoring workflows used by researchers.
- Design researcher-facing libraries, interfaces, and command-line tools.
- Build correctness and sanity checking into the infrastructure stack.
- Move high-value research workflows from experiments to reliable production-grade jobs.
- Improve the throughput, cost, and reliability of large-scale inference and scoring workloads.
- Partner with Safeguards researchers and engineers to anticipate evolving workflow needs.
Requirements
- Strong software engineering fundamentals and hands-on coding ability with proficiency in Python.
- Experience building and operating data-intensive or distributed systems in production.
- Experience building tooling or infrastructure used as a dependency by engineers or researchers.
- Comfort working across the research-to-deployment pipeline, from exploratory experiments to production systems.
- Ability to debug performance and correctness problems across an unfamiliar stack.
- Strong written and verbal communication skills and a collaborative approach to technical decisions.
- Experience with high-performance, large-scale machine learning systems is preferred.
- Familiarity with language modeling and transformers, including model internals, is preferred.
- Experience with machine learning framework internals, GPU or accelerator programming, or inference optimization is preferred.
- Experience building experiment tracking, caching layers, or evaluation harnesses for research teams is preferred.
- Experience with probes, interpretability, or classifier development is preferred.
- Interest in AI misuse risks and mitigating them is preferred.
- A bachelor’s degree or an equivalent combination of education, training, and/or experience is required.
- The required field of study must be relevant to the role as demonstrated through coursework, training, or professional experience.
Benefits
- Annual compensation range of $350,000–$500,000 USD.
- Hybrid policy requiring staff to work from an office at least 25% of the time, with some roles requiring more.
- Visa sponsorship and immigration-lawyer support may be available.
- Competitive benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.
Tech Stack
Categories
About Anthropic
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.