Research Engineer, Model Evaluations at Anthropic

San Francisco, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine LearningIndustries

Requirements

Experience designing and implementing evaluation systems for machine learning models, particularly large language models
Demonstrated technical leadership experience, either formally or through leading complex technical projects
Skilled at both systems engineering and experimental design, comfortable building infrastructure while maintaining scientific rigor
Strong programming skills in Python and experience with distributed computing frameworks
Ability to translate between research needs and engineering constraints, finding pragmatic solutions to complex problems
Results-oriented and thrive in fast-paced environments where priorities can shift based on research findings
Enjoy collaborative work and can effectively communicate technical concepts to diverse stakeholders
Care deeply about AI safety and the societal impacts of the systems we build
Experience with statistical analysis and can draw meaningful conclusions from large-scale experimental data

Responsibilities

Design novel evaluation methodologies to assess model capabilities across diverse domains including reasoning, safety, helpfulness, and harmlessness
Lead the design and architecture of Anthropic's evaluation platform, ensuring it scales with our rapidly evolving model capabilities and research needs
Implement and maintain high-throughput evaluation pipelines that run during production training, providing real-time insights to guide training decisions
Analyze evaluation results to identify patterns, failure modes, and opportunities for model improvement, translating complex findings into actionable insights
Partner with research teams to develop domain-specific evaluations that probe for emerging capabilities and potential risks
Build infrastructure to enable rapid iteration on evaluation design, supporting both automated and human-in-the-loop assessment approaches
Establish best practices and standards for evaluation development across the organization
Mentor team members and contribute to the growth of evaluation expertise at Anthropic
Coordinate evaluation efforts during critical training runs, ensuring comprehensive coverage and timely results
Contribute to research publications and external communications about evaluation methodologies and findings

Skills

Key technologies and capabilities for this role

PythonML EngineeringEvaluation PlatformsPipeline DevelopmentData AnalysisModel EvaluationScalable SystemsReasoning EvaluationSafety EvaluationInfrastructure DesignReal-time SystemsResearch Collaboration

Questions & Answers

Common questions about this position

What programming skills are required for this role?

Strong programming skills in Python are required.

What experience is needed for the Research Engineer position?

Experience designing and implementing evaluation systems for machine learning models, particularly large language models, and demonstrated technical leadership experience are required. Candidates should also be skilled at both systems engineering and experimental design.

Is this role remote or office-based?

This information is not specified in the job description.

What is the salary or compensation for this position?

This information is not specified in the job description.

What makes a strong candidate for this role?

You may be a good fit if you have experience with ML model evaluations, technical leadership, skills in systems engineering and experimental design, and strong Python programming.

Anthropic

Develops reliable and interpretable AI systems

About Anthropic

Anthropic focuses on creating reliable and interpretable AI systems. Its main product, Claude, serves as an AI assistant that can manage tasks for clients across various industries. Claude utilizes advanced techniques in natural language processing, reinforcement learning, and code generation to perform its functions effectively. What sets Anthropic apart from its competitors is its emphasis on making AI systems that are not only powerful but also understandable and controllable by users. The company's goal is to enhance operational efficiency and improve decision-making for its clients through the deployment and licensing of its AI technologies.

San Francisco, CaliforniaHeadquarters

2021Year Founded

$11,482.1MTotal Funding

GROWTH_EQUITY_VCCompany Stage

Enterprise Software, AI & Machine LearningIndustries

1,001-5,000Employees

Benefits

Flexible Work Hours

Paid Vacation

Parental Leave

Hybrid Work Options

Company Equity

Risks

Ongoing lawsuit with Concord Music Group could lead to financial liabilities.

Technological lag behind competitors like OpenAI may impact market position.

Reliance on substantial funding rounds may indicate financial instability.

Differentiation

Anthropic focuses on AI safety, contrasting with competitors' commercial priorities.

Claude, Anthropic's AI assistant, is designed for tasks of any scale.

Partnerships with tech giants like Panasonic and Amazon enhance Anthropic's strategic positioning.

Upsides

Anthropic's $60 billion valuation reflects strong investor confidence and growth potential.

Collaborations like the Umi app with Panasonic tap into the growing wellness AI market.

Focus on AI safety aligns with increasing industry emphasis on ethical AI development.

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