Anthropic
AI Frontier · AI lab
- HQ
- San Francisco, US
- Founded
- 2021
- Size
- 1,500+
- Website
- anthropic.com
- Blog
- anthropic.com
Products
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.
AI Frontier · AI lab
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 24 new AI-related roles. That is a -27% change versus the prior 30 days (33 → 24).
| Title | Stage | AI score |
|---|---|---|
| Research Engineer, RL Scaling Science Research Engineer focused on scaling Reinforcement Learning (RL) for frontier models. Designs and runs large-scale RL experiments to understand and resolve bottlenecks, builds benchmarks for long-horizon progress, and ships validated findings into production training recipes. Operates at the research/engineering boundary. | Post-trainPretrain | 10 |
| Research Engineer, Pretraining Research Engineer focused on pretraining large language models, involving research into model architecture, algorithms, data processing, and optimizers, along with scaling training infrastructure and analyzing experiments. The role contributes to the entire stack from low-level optimizations to high-level model design. |
| Pretrain |
| 10 |
| Research Engineer, Machine Learning (Reinforcement Learning) Research Engineer focused on Reinforcement Learning to advance capabilities and safety of large language models. This role involves implementing novel approaches, contributing to research direction, and creating agentic models for tasks like computer use and autonomous software generation, while also improving reasoning abilities and developing prototypes. Key responsibilities include architecting RL infrastructure, designing training environments and methodologies, driving performance improvements, and collaborating across teams. | AgentPost-train | 10 |
| Research Engineer, Machine Learning (RL Velocity) The RL Velocity team owns the efficiency and reliability of the RL Science stack, building and improving the core platform for RL training runs to remove bottlenecks and enable faster iteration. This role focuses on ML infrastructure, distributed systems, and research tooling to improve the velocity and reliability of RL training at scale. | DataPost-train | 9 |
| Anthropic Fellows Program — Reinforcement Learning This is a research fellowship program focused on Reinforcement Learning (RL) within AI safety. Fellows will work on empirical projects, potentially using external infrastructure, with the goal of producing public outputs like paper submissions. The program emphasizes mentorship from Anthropic researchers and provides a stipend and compute funding. Key activities include building model-based tools for data quality, understanding generalization, and creating RL environments for capabilities and safety tasks. | Post-train | 9 |
| Anthropic Fellows Program — AI Safety This is a research fellowship program focused on AI safety, aiming to foster talent in empirical AI research. Fellows will work on projects aligned with Anthropic's research priorities, using external infrastructure and external models, with the goal of producing public outputs like paper submissions. Key research areas include Scalable Oversight, Adversarial Robustness and AI Control, Model Organisms, Model Internals / Mechanistic Interpretability, and AI Welfare. | Post-train | 9 |
| Anthropic Fellows Program — AI Security This is a research fellowship program focused on AI safety and security, aiming to produce public outputs like paper submissions. Fellows will use external infrastructure and open-source models, working on empirical projects with mentorship from Anthropic researchers. | Post-train | 9 |
| Anthropic Fellows Program Anthropic's Fellows Program offers a 4-month full-time research opportunity focused on AI safety and related areas. Fellows will use external infrastructure and open-source models to conduct empirical projects, aiming for public outputs like paper submissions, with mentorship from Anthropic researchers. The program is designed to foster AI research and engineering talent, regardless of previous experience, and emphasizes safety, interpretability, and steerability of AI systems. | Pretrain | 9 |
| Research Engineer, Pretraining Scaling - London Research Engineer focused on pretraining and scaling large language models, involving performance optimization, debugging, experimental design, and ensuring reliability of production training pipelines. The role is highly operational, requiring on-call incident response during model launches, and involves building and maintaining training infrastructure and codebase capabilities. | Pretrain | 9 |
| Research Engineer / Scientist, Alignment Science - London Research Engineer/Scientist focused on AI safety and alignment, conducting experimental research to understand and steer the behavior of powerful AI systems. The role involves testing robustness of safety techniques, running multi-agent RL experiments, building tooling for evaluating jailbreaks, and contributing to research papers. Collaboration with Interpretability, Fine-Tuning, and Frontier Red Team is expected. | Post-trainEval Gate | 9 |
| 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 |
| Technical Specialist, Claude Code This role focuses on driving adoption of Anthropic's Claude Code product within enterprise customers. It involves technical enablement, running workshops, supporting pilots, building demo applications, and gathering field feedback to inform product development. The role requires a strong technical voice and the ability to engage with developers and department leaders on AI coding tools and agentic workflows. | Agent | 7 |
| Regional Research Economist, Economic Research Research Economist focused on measuring and understanding AI's economic impact, developing new methodologies, and collaborating with external partners on policy interventions. Utilizes frontier econometrics, machine learning, and structural estimation methods. | 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 |
| Staff Software Engineer, AI Reliability Engineering Staff Software Engineer, AI Reliability Engineering at Anthropic. This role focuses on improving the reliability, robustness, and resilience of AI serving systems, specifically for large language models like Claude. Responsibilities include developing SLOs, designing monitoring and observability, assisting with high-availability infrastructure, leading incident response for critical AI services, and supporting the reliability of safeguard model serving. | Serve | 7 |
| Software Engineer, Safeguards Infrastructure Software Engineer focused on building foundational systems for AI safety, including infrastructure for data management, metric and evaluation systems, and tooling for human and agentic review. The role involves ensuring the day-to-day running of Safeguards systems and building robust, reliable multi-layered defenses for real-time improvement of safety mechanisms at scale. | Eval GateAgent | 7 |