обновлено 8 дней назад
ML/Research Engineer (AI Safeguards)
350 000 - 500 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
ML/Research Engineer (AI Safeguards) (Machine Learning/AI Safety): Building classifiers, synthetic data pipelines, monitoring systems, and defenses that detect misuse, coordinated attacks, anomalous behavior, and agentic risks with an accent on large-scale ML systems, safety evaluation, and adversarial robustness. Focus on developing threat models and testing environments, aggregating signals across contexts, mitigating prompt injection attacks, and conducting automated red-teaming research.
Location: San Francisco, CA or New York City, NY; hybrid policy requires staff to work from one of the offices at least 25% of the time
Annual salary: $350,000–$500,000 USD
Company
Anthropic develops reliable, interpretable, and steerable AI systems designed to be safe and beneficial for users and society.
What you will do
- Develop classifiers, synthetic data pipelines, and automated evaluation methods to detect misuse and anomalous behavior at scale.
- Build monitoring systems for harms spanning multiple exchanges, including coordinated cyber attacks and influence operations.
- Aggregate and analyze signals across contexts to identify sophisticated misuse patterns.
- Evaluate and improve the safety of agentic products by developing threat models, testing environments, and mitigations for prompt injection attacks.
- Conduct research in automated red-teaming, adversarial robustness, and methods for finding and preventing misuse.
Requirements
- 4+ years of experience in ML engineering, research engineering, or applied research in academia or industry.
- Proficiency in Python and experience building machine learning systems.
- Ability to work across the research-to-deployment pipeline, from exploratory experiments to production systems.
- Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
- Bachelor’s degree or equivalent education, training, or professional experience in a relevant field.
Nice to have
- Experience with language modeling and transformers.
- Experience building classifiers, anomaly detection systems, or behavioral ML systems.
- Background in adversarial machine learning, red-teaming, interpretability, probes, or reinforcement learning.
- Experience with high-performance, large-scale ML systems.
Culture & Benefits
- Collaborative research environment focused on large-scale AI safety efforts.
- Frequent research discussions and cross-functional collaboration with researchers, engineers, policy experts, and business leaders.
- Visa sponsorship is available, with reasonable efforts and immigration lawyer support for successful candidates.
- Competitive compensation, optional equity donation matching, generous vacation and parental leave, and flexible working hours.
- Office-based collaboration in San Francisco or New York under the hybrid policy.
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