Anthropic
Staff Machine Learning Engineer, Agent Skills
Anthropic, San Francisco, California, United States, 94199
Staff Machine Learning Engineer, Agent Skills
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Staff Machine Learning Engineer, Agent Skills
role at
Anthropic .
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 society as a whole. Our team is a quickly growing group of researchers, engineers, policy experts, and business leaders building beneficial AI systems.
About The Role Agent systems are the next frontier of usefulness for Claude. Over the last year, we’ve seen rapid adoption of Claude-powered agent systems in coding, research, customer support, network security, and more. We aim to make Claude an even more effective agent, focusing on planning, reliable execution, tool use, memory, and inter-agent coordination. We strive to maximize agent performance by solving challenges at whatever level is needed, whether it’s fine-tuning, agent infrastructure, or design best practices. We ask you to share a project built on LLMs showcasing complex task execution.
Responsibilities
Finetune new capabilities into Claude that maximize performance or ease of use on agentic tasks.
Ideate, develop, and compare performance of different tools for agents (e.g., memory, context compression, communication architectures).
Develop and improve the virtual machine infrastructure and affordances that Claude has access to.
Systematically discover and test best practices for creating and using Agent Skills.
Develop automated techniques for designing and evaluating agentic systems.
Assist with automated evaluation of Claude models and prompts across the training and product lifecycle.
Work with product org to find solutions to challenges applying agents to our products.
Help create and optimize data mixes for model training.
You May Be a Good Fit If You
Have 7+ years of ML and software engineering experience.
Have a high level familiarity with the architecture and operation of large language models.
Have extensive prior experience exploring and testing language model behavior.
Have spent time prompting and/or building products with language models.
Have good communication skills and an interest in working with other researchers on difficult tasks.
Have a passion for making powerful technology safe and societally beneficial.
Stay up-to-date and informed by actively following emerging research and industry trends.
Enjoy pair programming.
Strong Candidates May Also Have Experience With
Developing complex agentic systems using LLMs.
Large-scale reinforcement learning on language models.
Multi-agent systems.
Representative Projects
Implementing and testing a novel retrieval, tool use, sub-agent, or memory architecture for Claude.
Finetuning Claude to maximize performance using a particular set of agent tools.
Designing and validating pipelines for creating Agent Skills for specific use cases with measurable improvements.
Building evaluation frameworks to test Agent Skills effectiveness across diverse workflows.
Building and testing automated systems for Agent Skills creation.
Compensation Annual salary: $340,000—$560,000 USD. Total compensation includes equity, benefits, and may include incentive compensation.
Logistics Education Requirements:
Bachelor’s degree in a related field or equivalent experience.
Location-based hybrid policy:
Expect all staff to be in one of our offices at least 25% of the time; some roles may require more time in the office.
Visa sponsorship:
We sponsor visas where possible and will make every reasonable effort to facilitate immigration.
We encourage you to apply even if you do not meet every qualification. Representation and diversity are important to us.
How We’re Different: We focus on high-impact research, value impact over narrow puzzles, and value communication skills. Our culture is collaborative with frequent research discussions.
Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation, benefits, optional equity donation matching, vacation, parental leave, flexible hours, and a lovely office space.
#J-18808-Ljbffr
Staff Machine Learning Engineer, Agent Skills
role at
Anthropic .
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 society as a whole. Our team is a quickly growing group of researchers, engineers, policy experts, and business leaders building beneficial AI systems.
About The Role Agent systems are the next frontier of usefulness for Claude. Over the last year, we’ve seen rapid adoption of Claude-powered agent systems in coding, research, customer support, network security, and more. We aim to make Claude an even more effective agent, focusing on planning, reliable execution, tool use, memory, and inter-agent coordination. We strive to maximize agent performance by solving challenges at whatever level is needed, whether it’s fine-tuning, agent infrastructure, or design best practices. We ask you to share a project built on LLMs showcasing complex task execution.
Responsibilities
Finetune new capabilities into Claude that maximize performance or ease of use on agentic tasks.
Ideate, develop, and compare performance of different tools for agents (e.g., memory, context compression, communication architectures).
Develop and improve the virtual machine infrastructure and affordances that Claude has access to.
Systematically discover and test best practices for creating and using Agent Skills.
Develop automated techniques for designing and evaluating agentic systems.
Assist with automated evaluation of Claude models and prompts across the training and product lifecycle.
Work with product org to find solutions to challenges applying agents to our products.
Help create and optimize data mixes for model training.
You May Be a Good Fit If You
Have 7+ years of ML and software engineering experience.
Have a high level familiarity with the architecture and operation of large language models.
Have extensive prior experience exploring and testing language model behavior.
Have spent time prompting and/or building products with language models.
Have good communication skills and an interest in working with other researchers on difficult tasks.
Have a passion for making powerful technology safe and societally beneficial.
Stay up-to-date and informed by actively following emerging research and industry trends.
Enjoy pair programming.
Strong Candidates May Also Have Experience With
Developing complex agentic systems using LLMs.
Large-scale reinforcement learning on language models.
Multi-agent systems.
Representative Projects
Implementing and testing a novel retrieval, tool use, sub-agent, or memory architecture for Claude.
Finetuning Claude to maximize performance using a particular set of agent tools.
Designing and validating pipelines for creating Agent Skills for specific use cases with measurable improvements.
Building evaluation frameworks to test Agent Skills effectiveness across diverse workflows.
Building and testing automated systems for Agent Skills creation.
Compensation Annual salary: $340,000—$560,000 USD. Total compensation includes equity, benefits, and may include incentive compensation.
Logistics Education Requirements:
Bachelor’s degree in a related field or equivalent experience.
Location-based hybrid policy:
Expect all staff to be in one of our offices at least 25% of the time; some roles may require more time in the office.
Visa sponsorship:
We sponsor visas where possible and will make every reasonable effort to facilitate immigration.
We encourage you to apply even if you do not meet every qualification. Representation and diversity are important to us.
How We’re Different: We focus on high-impact research, value impact over narrow puzzles, and value communication skills. Our culture is collaborative with frequent research discussions.
Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation, benefits, optional equity donation matching, vacation, parental leave, flexible hours, and a lovely office space.
#J-18808-Ljbffr