Anthropic Research Resident
Anthropic · San Francisco, CA | New York City, NY · AI Research & Engineering · listed October 28, 2026
The shape of it
Seniority
Not stated
Where
Remote
Stated pay
$350,000 – $500,000
Requirements listed
5
Length
1,421 words
In the posting’s own words
The Anthropic Residency is our paid, fixed-term research program, with placements lasting between six weeks and six months. We are looking for people who have led ambitious work in a variety of technical fields and want to transition to full-time work focused on making sure AI systems are safe and beneficial for all of humanity. If you are a professor in a quantitative discipline, a technical founder or a staff-level engineer and want to transition to work on transformative AI, we want to hear from you. Background in machine learning is not required.
What it asks for · 5
- Are motivated by making sure AI is safe and beneficial for society as a whole
- Are excited to transition into working on empirical AI research full-time
- Have led ambitious work in a variety of technical fields (professor in a quantitative discipline, a technical founder or a staff-level engineer)
- Thrive in fast-paced, collaborative environments
- Can implement ideas quickly and communicate clearly
Also a plus
- Have experience authoring research papers in machine learning, NLP, or AI safety
- Have experience with LLMs, reinforcement learning or Kubernetes clusters and complex shared codebases
Tools and skills named
Models & research
- Machine learning5×
- LLM2×
- NLP2×
- Reinforcement learning2×
- Evaluations
- GPU
Security & compliance
- Security3×
- Cryptography
Ways of working
- Testing2×
- Mentorship
Cloud & infra
- Kubernetes
Words the posting leans on
- models14×
- research12×
- background9×
- safety7×
- alignment6×
- technical6×
- leads5×
- adversarial4×
- frontier4×
- machine learning4×
- systems4×
- developing3×
- interpretability3×
- language models3×
- potential3×
- researches3×
Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.
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