Overview
Anthropic is hiring a Research Engineer / Research Scientist in Zurich for its Pre-training team working on next-generation large language models and multimodal capabilities.
Full job description
The role combines frontier research and practical engineering across model architecture, algorithms, data pipelines, optimizer development, scientific experimentation, distributed training infrastructure, fault tolerance and developer tooling. Anthropic states that staff are generally expected to be in an office at least 25% of the time. The posting also states that Anthropic sponsors visas, although sponsorship cannot be guaranteed for every role or candidate.
Requirements & qualifications
Anthropic seeks candidates with at least a bachelor's degree or equivalent relevant experience, strong software-engineering skills, Python and deep-learning expertise, and experience with large-scale machine-learning systems. The posting highlights model architecture, algorithms, data processing, optimizers, distributed training, ML accelerators, Kubernetes and large-scale data processing; an MS or PhD is preferred but not required.
Tips for this job
Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Verification notes
Verified against the live Anthropic Greenhouse posting, which currently has an Apply action. The page states Zurich as the location, outlines pre-training and multimodal LLM responsibilities, and explicitly says Anthropic sponsors visas while noting that sponsorship may not succeed for every role or candidate. No salary or closing date is stated.
Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
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