Anthropic has 145 active AI-related job listings. The majority of these roles are focused on agents, comprising 28% of the total. Engineering is the most frequent function, with 74 listings, followed by Research with 51. The company is primarily hiring in the United States, with 118 positions, and the United Kingdom, with 22. Frequent tech tags include model_serving, evals, and agent_orchestration, suggesting a focus on deployment and evaluation of AI systems. In the last 30 days, Anthropic posted 16 new AI roles, a 47% decrease compared to the previous 30-day period.
Currently tracking 124 active AI roles, with 106 new openings in the last 4 weeks. Primary focus: Agent · Engineering. Salary range $46k–$850k (avg $405k).
Anthropic currently has 132 active AI-related roles in our index. The most common open titles are: Applied AI Architect, Industries (2), 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). Most positions are in Engineering and Research.
Anthropic's active AI hiring is concentrated in: agents (28%), serving infrastructure (17%), post-training (14%). 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 (106 roles), United Kingdom (20 roles), Canada (6 roles), Ireland (5 roles).
Job postings at Anthropic most frequently reference: model serving, evals, llm observability, agent orchestration, inference infra.
In the past 30 days, Anthropic has posted 29 new AI-related roles. That is a +61% change versus the prior 30 days (18 → 29).
| Title | Stage | AI score |
|---|---|---|
| Research Engineer, Science of Scaling Research Engineer/Scientist on the Science of Scaling team, focused on developing next-generation large language models. The role involves research at the intersection of cutting-edge research and practical engineering, contributing to safe, steerable, and trustworthy AI systems. Responsibilities include research into the science of converting compute into intelligence, leading research projects, designing and analyzing experiments, optimizing training infrastructure, and developing dev tooling. Requires significant software engineering experience, proficiency in Python and deep learning frameworks, and a results-oriented approach. Strong candidates may have experience with JAX, reinforcement learning, high-performance ML systems, accelerators, Kubernetes, OS internals, transformer architectures, large-scale ETL, and distributed training at scale. | Pretrain | 10 |
| Research Engineer / Research Scientist, Pre-training |
| Pretrain |
| 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, Pretraining Scaling Research Engineer focused on training production pretrained models at scale, involving performance optimization, debugging, experimental design, and incident response during model launches. The role bridges research and engineering, working across the full training stack. | Pretrain | 10 |
| Anthropic AI Safety Fellow, UK This is a research fellowship focused on AI safety, aiming to produce empirical research outputs like paper submissions. Fellows will use external infrastructure and work on projects aligned with Anthropic's research priorities, receiving mentorship and resources. | Pretrain | 10 |
| Research Engineer/Research Scientist, Pre-training Research Engineer/Scientist focused on pre-training large language models, involving research in model architecture, algorithms, data processing, and optimizer development, as well as optimizing and scaling training infrastructure. | Pretrain | 10 |
| Research Engineer / Research Scientist, Pre-training Research Engineer/Scientist focused on pre-training large language models, with an emphasis on multimodal capabilities. The role involves research, implementation, experiment design, and optimizing training infrastructure for next-generation AI systems. | Pretrain | 10 |
| Staff Research Engineer, Discovery Team Staff Research Engineer focused on building AI systems capable of scientific discovery and long-horizon reasoning, working across the full model stack from training to inference and agentic systems. | PretrainAgent | 10 |
| Research Scientist / Research Engineer, Pre-training Research Engineer role focused on pre-training large language models, involving research into model architecture, algorithms, data processing, and optimizer development, alongside optimizing and scaling training infrastructure. Requires advanced degree, strong software engineering skills, and expertise in Python and deep learning frameworks. | Pretrain | 10 |
| 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 / Research Scientist, Tokens Research Engineer/Scientist role focused on building large-scale ML systems, touching all parts of code and infrastructure, from cluster reliability and job efficiency to running scientific experiments and improving dev tooling. The role involves optimizing ML systems, comparing model variants, scaling training jobs, and designing fault tolerance strategies, with a focus on safe, steerable, and trustworthy AI. | PretrainServe | 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 Manager, Tokens Research Manager for the Pretraining Data team (Tokens) at Anthropic. Focuses on understanding and innovating pretraining data for foundational AI models, including data trends, scaling laws, data sources, and processing methodologies. Leads a team of researchers and engineers. | Pretrain | 9 |
| Research Scientist / Research Engineer, Pre-training Research Engineer role focused on the pre-training of large language models, involving research into model architecture, algorithms, data processing, and optimizer development, as well as scaling training infrastructure and developing dev tooling. Requires advanced degree, strong software engineering skills, and familiarity with large-scale ML and deep learning frameworks. | Pretrain | 9 |
| Research Engineer, Tokens ML Infra Research Engineer focused on ML training infrastructure for large language models, involving JAX/PyTorch, distributed systems, performance optimization, and MLOps tooling to support novel training architectures and experimentation. | Pretrain | 9 |
| Research Engineer / Research Scientist, Multimodal Research Engineer/Scientist focused on building and studying multimodal AI systems, including training, inference, system design, and data collection. The role involves developing new architectures, reinforcement learning environments, high-performance serving infrastructure, and data processing tools for multimodal data. | PretrainPost-train | 9 |
| Research Scientist, Tokens (Multimodal) Research Scientist focused on multimodal AI systems, working on training, inference, system design, and data collection. The role involves developing new architectures for multimodal data, building infrastructure for RL environments and RPC servers, and collecting/processing large-scale multimodal data. Emphasis on foundational research and large-scale experiments. | PretrainPost-train | 9 |
| Research Engineer, Tokens (Pre-training) Research Engineer focused on pretraining data for large-scale AI models. Responsibilities include understanding data trends, scaling laws, optimizing data mixes, exploring new data sources, building research tools for analysis, and effective data processing. Strong software engineering and empirical research skills are required. | Pretrain | 9 |
| Research Manager, Horizons Research Manager for the Horizons team at Anthropic, focusing on RL with LLMs, code generation, reasoning, tool use, and agents. The role involves team management, project planning, vision-setting, people development, and ensuring execution aligns with AI safety goals. | Pretrain | 9 |