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Research Engineer, Cybersecurity RL (Reinforcement Learning)

Label Your Data·$500,000 – $850,000

Primary stack

Machine Learning

Nice to have's

RL techniquesLLM training methodologiessecurity engineering

Job description

About the Position

Research Engineer, Cybersecurity RL (Reinforcement Learning)

San Francisco, CA | New York City, NY


About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.


About Horizons

The Horizons team leads Anthropic's reinforcement learning (RL) research and development, playing a critical role in advancing our AI systems. We've contributed to every Claude release, with significant impact on the autonomy, coding, and reasoning capabilities of Anthropic's models.


About the Role

We're hiring for the Cybersecurity RL team within Horizons. As a Research Engineer, you'll help to safely advance the capabilities of our models in secure coding, vulnerability remediation, and other areas of defensive cybersecurity.

This role blends research and engineering, requiring you to both develop novel approaches and realize them in code. Your work will include designing and implementing RL environments, conducting experiments and evaluations, delivering your work into production training runs, and collaborating with other researchers, engineers, and cybersecurity specialists across and outside Anthropic.

The role requires domain expertise in cybersecurity paired with interest or experience in training safe AI models. For example, you might be a white hat hacker who's curious about how LLMs could augment or transform your work, a security engineer interested in how AI could help harden systems at scale, or a detection and response professional wondering how models could enhance defensive workflows.


You May Be a Good Fit If You:

  • Have experience in cybersecurity research.
  • Have experience with machine learning.
  • Have strong software engineering skills.
  • Can balance research exploration with engineering implementation.
  • Are passionate about AI's potential and committed to developing safe and beneficial systems.

Strong Candidates May Also Have:

  • Professional experience in security engineering, fuzzing, detection and response, or other applied defensive work.
  • Experience participating in or building CTF competitions and cyber ranges.
  • Academic research experience in cybersecurity.
  • Familiarity with RL techniques and environments.
  • Familiarity with LLM training methodologies.

Annual Salary

$500,000-$850,000 USD


Logistics

  • Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
  • Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
  • Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
  • Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
  • Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We Encourage You to Apply

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.


Your Safety Matters to Us

To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links-visit anthropic.com/careers directly for confirmed position openings.


How We're Different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact - advancing our long-term goals of steerable, trustworthy AI - rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.


Come Work with Us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

© Label Your Data. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.

Label Your Data provides secure and high quality data annotation services for Computer Vision or NLP applications since 2020. We help Data Scientists and AI Engineers streamline the dataset labeling and focus on model development.About Label Your Data:— Founded in 2020;— 200+ annotation experts in Europe, LATAM and Africa;— 98%+ annotation accuracy benchmark;— 55 supported languages;— PCI/DSS certified;— ISO/IEC 27001:2013 certified;— GDPR, CCPA and HIPAA-compliant;— HQs in North America, EU and Asia.Our experience spans over 20 industries including Automotive, Robotics, Agriculture, E-commerce, Retail, Healthcare, Manufacturing, Fintech and Insurance.Our core services include but are not limited to:— Image & video annotation: 2D boxes, OCR, object/action detection, polygons, key points, semantic segmentation, 3D cuboids;— Text annotation: classification, NER, intent & sentiment analysis, prompts creation, Q&A pairs generation;— Audio annotation: transcription, sentiment recognition;— Sensor data annotation;— Data classification & categorization;— Data entry;— Data collection;— Model validation.

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