Joblaze summary

In this role, the Research Engineer in Alignment Science at Anthropic focuses on designing and executing machine learning experiments aimed at enhancing AI safety and alignment. Key skills include software engineering, machine learning, and familiarity with AI safety research, particularly in the context of advanced AI systems. This position is ideal for individuals with a strong background in empirical AI research and a collaborative mindset, as the team emphasizes teamwork and communication in their mission to create beneficial AI. Anthropic's approach is rooted in large-scale research efforts, fostering a cohesive environment for impactful work.

Joblaze insights

Listed about 6 months ago — first seen on Joblaze April 14, 2026. Last confirmed on Anthropic's careers page October 30, 2026.
Salary band is above the typical range for AI/ML roles (median ~$190,000).
Starts above 96% of 209 comparable senior ai/ml roles in United States that list Python we track (median $182,000 across 70 companies). See Python salary trends
Python appears in 53.4% of 560 comparable senior ai/ml roles in United States; NLP appears in 1.6% of 560 comparable senior ai/ml roles in United States.

Quick facts

Is the Research Engineer / Scientist, Alignment role remote?: It's hybrid — Anthropic expects some on-site time in San Francisco, CA.
What's the salary range?: Anthropic lists $350,000–$500,000 for this role.
Where is the role based?: Anthropic is hiring for this position in San Francisco, CA.
What's the tech stack?: Joblaze extracted these technologies from the posting: AI Safety, Kubernetes, LLMs, Machine Learning, NLP, Python.
Does Anthropic sponsor work visas for this role?: Yes — the posting indicates visa sponsorship is available for the right candidate.
What seniority level is this role?: Anthropic targets senior candidates for this position.
Is this full-time or contract?: Full-time for this Research Engineer / Scientist, Alignment role at Anthropic.

From the original posting

About Anthropic

About the role:

You want to build and run elegant and thorough machine learning experiments to help us understand and steer the behavior of powerful AI systems. You care about making AI helpful, honest, and harmless, and are interested in the ways that this could be challenging in the context of human-level capabilities. You could describe yourself as both a scientist and an engineer. As a Research Engineer on Alignment Science, you'll contribute to exploratory experimental research on AI safety, with a focus on risks from powerful future systems (like those we would designate as ASL-3 or ASL-4 under our Responsible Scaling Policy), often in collaboration with other teams including Interpretability, Fine-Tuning, and the Frontier Red Team.

Our blog provides an overview of topics that the Alignment Science team is either currently exploring or has previously explored. Our current topics of focus include...

Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains.
AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios.
Alignment Stress-testing: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise.
Automated Alignment Research: Building and aligning a system that can speed up & improve alignment research.
Alignment Assessments: Understanding and documenting the highest-stakes and most concerning emerging properties of models through pre-deployment alignment and welfare assessments (see our Claude 4 System Card), misalignment-risk safety cases, and coordination with third-party evaluators.
Safeguards Research: Developing robust defenses against adversarial attacks, comprehensive evaluation frameworks for model safety, and automated systems to detect and mitigate potential risks before deployment.
Model Welfare: Investigating and addressing potential model welfare, moral status, and related questions. See our program announcement and welfare assessment in the Claude 4 system card for more.

Note: For this role, we conduct all interviews in Python and prefer candidates to be based in the Bay Area.

Representative projects:

Testing the robustness of our safety techniques by training language models to subvert our safety techniques, and seeing how effective they are at subverting our interventions.
Run multi-agent reinforcement learning experiments to test out techniques like AI Debate.
Build tooling to efficiently evaluate the effectiveness of novel LLM-generated jailbreaks.
Write scripts and prompts to efficiently produce evaluation questions to test models’ reasoning abilities in safety-relevant contexts.
Contribute ideas, figures, and writing to research papers, blog posts, and talks.
Run experiments that feed into key AI safety efforts at Anthropic, like the design and implementation of our Responsible Scaling Policy.

You may be a good fit if you:

Have significant software, ML, or research engineering experience
Have some experience contributing to empirical AI research projects
Have some familiarity with technical AI safety research
Prefer fast-moving collaborative projects to extensive solo efforts
Pick up slack, even if it goes outside your job description
Care about the impacts of AI

Strong candidates may also:

Have experience authoring research papers in machine learning, NLP, or AI safety
Have experience with LLMs
Have experience with reinforcement learning
Have experience with Kubernetes clusters and complex shared codebases

Candidates need not have:

100% of the skills needed to perform the job
Formal certifications or education credentials

The annual compensation range for this role is listed below.

Annual Salary:

$350,000—$500,000 USD

Logistics

Standard company text repeated across Anthropic's postings is omitted here.

Research Engineer / Scientist, Alignment