Job Description

Job Title: ML Engineer - AI Safety & Evaluation Location : San Jose, California Employment Type : Full-Time / Permanent Job Summary: What We’re Looking For ~7+ years of experience in applied machine learning, AI infrastructure, or safety-critical systems, with 3+ years in a senior or staff-level technical leadership role ~ Deep understanding of transformer-based architectures and experience building or evaluating safety interventions for LLMs ~ Proven expertise in analyzing and addressing adversarial behaviors, edge-case failures, and misuse scenarios ~ Demonstrated ability to guide long-term technical strategy, influence organizational direction, and mentor cross-functional teams ~ Strong written and verbal communication skills, with experience influencing technical direction at the org or platform level ~ field ~ Bachelors, Masters, or PhD in Computer Science, Machine Learning, or a related field Nice to Have Experience applying techniques such as reinforcement learning from human feedback (RLHF), adversarial training, or safety fine-tuning at scale Hands-on work designing prompt-level defenses, content filtering systems, or mechanisms to prevent jailbreaks and policy violations Contributions to AI safety research, industry standards, or open-source tools related to model robustness, alignment, or evaluation Familiarity with model governance frameworks, including safety policies, model cards, red teaming protocols, or risk classification methodologies

Job Tags

Permanent employment, Full time,

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