Principal ML Engineer - AI Safety & Evaluation
A10 Networks, Inc - San Francisco
Work at A10 Networks, Inc
Overview
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Overview
Principal ML Engineer - AI Safety & Evaluation
Join to apply for the Principal ML Engineer - AI Safety & Evaluation role at A10 Networks, Inc
Principal ML Engineer - AI Safety & Evaluation
Join to apply for the Principal ML Engineer - AI Safety & Evaluation role at A10 Networks, Inc
We’re looking for a Principal Engineer to lead the technical strategy and architecture for protecting foundation models against misuse—such as jailbreaks, prompt injection, toxic outputs, and custom policy violations. In this role, you’ll apply your expertise in scalable systems design, applied machine learning, and model-level defenses to build core infrastructure that ensures AI systems behave safely and responsibly in production. You’ll set technical direction and drive architectural decisions across a broad surface area of AI safety systems—designing safety interventions, integrating evaluation workflows, and developing models and tooling that detect and prevent harmful or non-compliant behavior. This role is ideal for someone who wants to work at the intersection of model behavior, product safety, and system engineering.
What You’ll Do
- Architect and lead the development of model-level defenses against jailbreaks, prompt injection, and custom policy violations
- Define and drive evaluation strategies, including adversarial testing and stress-testing pipelines, to identify safety weaknesses before deployment
- Set technical direction for scalable mitigation techniques such as safety-focused fine-tuning, prompt shielding, and post-processing methods to reduce harmful or non-compliant outputs
- Collaborate with red teamers and researchers to convert emerging threats into measurable evaluations and system-level safeguards
- Scale and improve human-in-the-loop pipelines for detecting toxic, biased, or non-compliant outputs
- Stay up to date with LLM safety research, jailbreak tactics, and adversarial trends, and apply insights to real-world defenses
- 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
- 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
Compensation: up to $246K USD
Seniority level
Seniority level
Associate
Employment type
Employment type
Full-time
Job function
Job function
Engineering and Information TechnologyIndustries
Software Development
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