Anthropic
AI Frontier · AI lab
- HQ
- San Francisco, US
- Founded
- 2021
- Size
- 1,500+
- Website
- anthropic.com
- Blog
- anthropic.com
Products
AI Frontier · AI lab
Currently tracking 127 active AI roles, down 32% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $46k–$850k (avg $406k).
Anthropic currently has 151 active AI-related job listings, with a significant focus on roles related to agents, which constitute 32% of their openings. Engineering is the most frequent function, followed by Research. The majority of their hiring is concentrated in the United States. Frequent technical tags include evals, model_serving, and agent_orchestration, suggesting a focus on the practical deployment and management of AI systems.
Anthropic currently has 149 active AI-related roles in our index. The most common open titles are: Regional Research Economist, Economic Research (2), Research Engineer, Machine Learning (RL Velocity) (2), Research Engineer, Production Model Post-Training (2), Staff Software Engineer, AI Reliability Engineering (2), Product Manager, Safeguards Rare Harms. Most positions are in Engineering and Research.
Anthropic's active AI hiring is concentrated in: agents (31%), serving infrastructure (15%), post-training (15%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Anthropic is hiring AI talent in: United States (130 roles), United Kingdom (18 roles), Canada (6 roles), Ireland (3 roles).
Job postings at Anthropic most frequently mention: Machine Learning, AI Safety, Production ML Systems, System Design, Large Language Models (LLMs).
In the past 30 days, Anthropic has posted 32 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Research Scientist, Life Sciences (Computational) Research Scientist role focused on computational biology, combining deep expertise with frontier AI capabilities to accelerate scientific discovery. Responsibilities include building and maintaining analysis pipelines for large-scale biological data, designing experiments, generating hypotheses, standing up computational infrastructure, and heavily using LLMs and agent frameworks. The role aims to establish how computational biology operates at Anthropic and guide the development of AI systems for biological research. | DataAgent | 9 |
| Research Engineer, Domain Scaling Research Engineer focused on scaling AI models for real-world knowledge work in domains like finance, healthcare, and legal. This role involves owning the end-to-end data strategy, from sourcing tasks to RL training, including designing reward signals, managing external data vendors, and developing QA frameworks to ensure environment quality and prevent reward hacking. It combines applied research with hands-on data work. |
| DataPost-train |
| 9 |
| Research Engineer, Machine Learning (RL Velocity) Research Engineer focused on building and improving the RL training infrastructure and tooling at Anthropic. The role involves identifying and removing bottlenecks in the RL stack, partnering with researchers and other engineering teams, and owning the reliability and performance of research runs to enable faster iteration and shipping of better models at scale. | DataPost-train | 9 |
| Research Engineer, Environment Scaling This role focuses on improving the intelligence of public models by building and managing RL training environments. It involves identifying tasks, designing reward signals, managing external data vendors, and evaluating model performance, combining ML research, data operations, and project management. | DataPost-train | 9 |
| Machine Learning Systems Engineer, Research Tools Machine Learning Systems Engineer focused on developing and optimizing encodings and tokenization systems for Anthropic's Finetuning workflows. This role acts as a bridge between Pretraining and Finetuning teams, building infrastructure crucial for model learning and data interpretation, impacting research progress and efficiency. | DataPost-train | 9 |
| Privacy Research Engineer, Safeguards Research Engineer focused on privacy for large language models, developing and auditing privacy-preserving training algorithms and techniques, and ensuring responsible data handling. | DataPost-train | 9 |
| Data Operations Manager, Human Data This role focuses on building and scaling data operations for research teams working on frontier AI capabilities, including RLHF, safety, tool use, and agentic workflows. The Data Operations Manager will own data strategy, manage vendor partnerships, and implement systems to ensure high-quality training data, directly impacting model performance on critical capabilities. | DataPost-train | 8 |
| Software Engineer, RL Data Software Engineer on the RL Data team responsible for building systems that produce high-quality reinforcement learning data for Claude. This includes data collection pipelines, human feedback tooling, execution environments, and quality assurance. The role involves end-to-end ownership of stack components, iterating on prompts and evals, developing QA frameworks, hardening execution environments, and collaborating with domain experts and operations partners. | DataPost-train | 8 |
| Full-Stack Software Engineer, Reinforcement Learning Full-Stack Software Engineer to build platforms, tools, and interfaces for environment creation, data collection, and training observability for RL. The role involves owning product surfaces end-to-end, iterating on data collection strategies, and partnering with researchers to ship reliable products. | DataEval Gate | 8 |
| Anthropic Fellows Program — ML Systems & Performance This is a research fellowship program focused on AI systems and performance, with the goal of producing public outputs like paper submissions. Fellows will work on empirical projects, potentially involving building ML systems, data pipelines, or infrastructure for accelerators, using external infrastructure and open-source models. | Data | 8 |
| Staff+ Software Engineer, Privacy Staff+ Software Engineer, Privacy at Anthropic. This role focuses on establishing and leading the privacy engineering function for AI systems, architecting privacy-preserving systems, implementing privacy-enhancing technologies, and providing technical leadership. It involves working at the intersection of privacy engineering, AI safety, and distributed systems, with responsibilities including designing privacy-preserving architectures for training and inference, building privacy infrastructure, translating regulations into technical implementations, and leading privacy reviews. The role requires experience with privacy engineering principles, Python/Go, production systems at scale, data governance, and privacy regulations. | DataServe | 7 |
| Product Management, Human Data Platform Product Manager for Anthropic's Human Data Platform, focusing on building systems to collect data that improves AI models. Responsibilities include owning product direction for data tooling, partnering with engineering, understanding research and training approaches, identifying patterns for reusable infrastructure, understanding vendor pain points, and defining KPIs related to data collection and model impact. | Data | 7 |
| Anthropic Fellows Program — The Anthropic Institute Fellows (Economics & Policy) This is a research fellowship program focused on empirical projects related to AI's economic and societal impacts, with the goal of producing public outputs like research papers. Fellows will use external infrastructure and work with mentors to explore areas such as AI's economic effects, labor markets, and AI-enabled cyber/bio capabilities. | Data | 7 |
| Software Engineer, Research Data Platform Software Engineer to build and operate data pipelines and tooling for AI researchers managing data from training runs, exploring datasets, and analyzing experiments. Focus on data products supporting the research workflow. | Data | 7 |
| Transformative AI Research Economist, Economic Research This role focuses on building macroeconomic models of transformative AI and developing scenario-based forecasting tools. It grounds projections in microeconomic data from the Anthropic Economic Index, analyzing millions of real-world AI interactions to understand AI's impact on labor markets, productivity, and economic transformation. The role also involves contributing to AI-powered research tools for economics. | Data | 7 |
| Research Economist, Economic Research Research Economist role focused on measuring and understanding the economic impact of AI systems, developing methodologies for the Anthropic Economic Index, and using frontier econometrics and machine learning methods. The role involves analyzing AI interactions, labor market impacts, and productivity, and translating insights into policy and product recommendations. | Data | 7 |