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

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