Sr. AI Engineer, Application Security

What You'll Do

• Secure-by-Design AI Architecture: Lead the design and implementation of AI systems with security as a core requirement — applying principles such as zero trust, least privilege, and continuous integrity verification
• Adversarial Defense & Robustness: Develop and deploy defenses against adversarial attacks (e.g., image perturbations, model inversion, data poisoning) in perception, prediction, and planning models
• Data Security & Privacy: Implement secure data pipelines for training and validation, including encryption, anonymization, access controls, and audit logging — especially for sensitive driving and user data
• Model Integrity & Provenance: Build systems to track model lineage, detect tampering, and ensure only trusted models are deployed in vehicles
• Secure CI/CD for AI: Design and maintain secure, automated pipelines for model training, testing, and over-the-air (OTA) deployment — integrating vulnerability scanning, container security, and policy enforcement
• Threat Modeling & Risk Assessment: Conduct regular security assessments of AI systems, including red teaming, attack surface analysis, and risk prioritization
• Incident Response & Forensics: Lead investigations into AI-related security incidents (e.g., model drift due to attack, data leakage, spoofing attempts) and drive post-mortems and remediation
• Internal Security Tooling: Develop and maintain tools for detecting model vulnerabilities, monitoring for anomalies, and automating security checks in AI workflows
• Cross-Functional Collaboration: Partner with Tesla’s Security, Compliance, Legal, and Product teams to ensure AI systems meet internal standards and regulatory requirements (e.g., ISO 21448 (SOTIF), NIST AI RMF, GDPR)
• Mentorship & Leadership: Guide junior engineers, conduct technical reviews, and lead security-focused initiatives across the AI engineering org

What You'll Bring

• Degree in Computer Science, Electrical Engineering, Mathematics, or a related field or equivalent experience
• 7+ years of professional software engineering experience, with at least 3 years focused on AI/ML systems in production environments
• Deep expertise in machine learning frameworks (PyTorch, TensorFlow) and their security implications (e.g., model extraction, inference leakage)
• Proven experience securing complex software systems: secure coding, authentication, API security, and vulnerability management
• Hands-on experience with AI security tools: IBM Adversarial Robustness Toolbox, Microsoft AI Fairness 360, TensorFlow Privacy, Evidently AI, or similar
• Solid understanding of cryptography (encryption, hashing, digital signatures) and its application in AI/ML systems
• Strong background in containerization (Docker, Kubernetes) and cloud platforms (AWS, GCP), including secure configuration and IAM
• Excellent communication, leadership, and problem-solving skills

Benefits

• Competitive pay
• Medical plans
• Fertility, adoption, and surrogacy benefits
• Dental and vision plans
• Health Savings Accounts (HSA)
• Short-term and long-term disability insurance
• Employee Assistance Program
• Voluntary benefits
• Employee discounts and perks

Pay

Expected Compensation $172,000 - $312,000/annual salary + cash and stock awards + benefits Pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered.