Research Engineer, Pretraining Scaling (London) at Anthropic

London, England, United Kingdom

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine Learning, TechnologyIndustries

Requirements

Hands-on experience training large language models, or deep expertise with JAX, TPU, PyTorch, or large-scale distributed systems
Enjoy both research and engineering work (ideal split roughly 50/50)
Excited about being on-call for production systems, working long days during launches, and solving hard problems under pressure
Thrive when working on whatever is most impactful, even if it changes day-to-day
Excel at debugging complex, ambiguous problems across multiple layers of the stack
Communicate clearly and collaborate effectively, especially across time zones or during high-stress incidents
Passionate about the work itself and want to refine your craft as a research engineer
Care about the societal impacts of AI and responsible scaling

Responsibilities

Own critical aspects of our production pretraining pipeline, including model operations, performance optimization, observability, and reliability
Debug and resolve complex issues across the full stack—from hardware errors and networking to training dynamics and evaluation infrastructure
Design and run experiments to improve training efficiency, reduce step time, increase uptime, and enhance model performance
Respond to on-call incidents during model launches, diagnosing problems quickly and coordinating solutions across teams
Build and maintain production logging, monitoring dashboards, and evaluation infrastructure
Add new capabilities to the training codebase, such as long context support or novel architectures
Collaborate closely with teammates across SF and London, as well as with Tokens, Architectures, and Systems teams
Contribute to the team's institutional knowledge by documenting systems, debugging approaches, and lessons learned

Skills

Machine Learning

Distributed Training

Performance Optimization

Hardware Debugging

Networking

Training Dynamics

Evaluation Infrastructure

Observability

Reliability Engineering

Monitoring Dashboards

Experimental Design

Production Pipelines

Model Operations

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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