Research Engineer, Discovery

Anthropic
San Francisco
Workplace: OnsiteFull timeFunction: Research & Scientific (R&D)Experience: 6+ yearsEducation: bachelorsSkills: ["Communication","Collaboration","Problem-solving"]

Research Engineer with end-to-end work across the model stack to remove infra blockers for scientific AGI. Focus on language model training, evaluation, and inference, distributed systems, VM/container deployment, and large-scale data pipelines. Collaborate with researchers to translate experimental needs into production infrastructure, optimizing training and inference pipelines for high-throughput ML workloads.

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Anthropic
Anthropic
1 year ago

Research Engineer, Discovery

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Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Research Engineer with end-to-end work across the model stack to remove infra blockers for scientific AGI. Focus on language model training, evaluation, and inference, distributed systems, VM/container deployment, and large-scale data pipelines. Collaborate with researchers to translate experimental needs into production infrastructure, optimizing training and inference pipelines for high-throughput ML workloads.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments
  • •Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities
  • •Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI
  • •Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows
  • •Collaborate to translate experimental requirements into production-ready infrastructure

Key Requirements

  • •6+ years of highly-relevant experience in infrastructure engineering with demonstrated expertise in large-scale distributed systems
  • •experience with containerization technologies (Docker, Kubernetes) and orchestration at scale
  • •proven track record of building large-scale data pipelines and distributed storage systems
  • •strong communication and collaboration skills
  • •experience with performance optimization techniques and system architectures for high-throughput ML workloads
Experience:6+ yearsAI researchMachine learningDistributed systems
Education:Bachelor's
Skills:CommunicationCollaborationProblem-solving
Languages:English
Tech Stack:DockerKubernetesPyTorchJAXBeamSparkDaskAWSGCPGPUTPU

Eligibility

Work Authorization:Sponsorship available.

Company Brief

Anthropic
Develops large-scale AI systems and safety research to create reliable, steerable, and interpretable AI assistants and models for commercial and research applications.
Industry: AI & Machine Learning
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series C
Headquarters: San Francisco, United States
Founded: 2021
WebsiteLinkedIn