Staff Software Developer, AI/ML Safety & Security – Waterloo / New York / Sunnyvale | Visa + Salary Insights

📍 Location: ca, us

🏷 Type: Full-time

Job Intelligence

📍 More in this location:
Browse AI jobs in ca

🏷 Similar roles:
View similar Full-time jobs

🌐 Explore all jobs:
View all AI job listings

Job Overview

This role sits within Google’s advanced AI Safety and Security engineering organization, focused on protecting GenAI-powered Workspace products such as Gmail, Docs, Drive, Meet, and Calendar. The position is designed for a highly experienced software engineer with deep expertise in large-scale machine learning systems, adversarial ML defense, and production-grade LLM infrastructure. The ideal candidate operates at the intersection of AI research and distributed systems engineering, building robust safeguards against prompt injection, abuse, and model exploitation while ensuring reliability at global scale across billions of users.

📅 Job Timeline & Status

This is an active, mid-cycle hiring role at Google with strong urgency due to its placement in core AI safety infrastructure. Given the strategic importance of GenAI security for Workspace products, applications are reviewed continuously. Candidates with strong ML systems and security backgrounds should apply immediately due to high global competition and limited openings in this specialized team.

🌍 Work Eligibility & Location

This role is internationally accessible for senior engineers, with strong support for relocation and global hiring pipelines. However, the position is fundamentally onsite-driven due to sensitive AI security infrastructure work requiring tight collaboration with DeepMind and Workspace engineering teams.

💰 Salary Intelligence

This is a top-tier compensation band reflecting Staff-level expectations in AI/ML security. The role includes significant equity and performance bonuses, placing it among the highest-paid ML security engineering positions in the industry. Compensation aligns with critical infrastructure ownership and production responsibility at global scale.

📊 Role Breakdown

This role focuses on building and scaling AI safety systems that protect GenAI workloads across Google Workspace. Engineers are expected to design large-scale ML pipelines, build LLM-based safety classifiers, and deploy real-time detection systems for adversarial behavior such as prompt injection attacks. Approximately 40% of the role is dedicated to ML system design and training pipeline optimization, 30% to security engineering and adversarial defense modeling, and 30% to distributed systems and production reliability.

You will work extensively with LLMs, multimodal models, and evaluation frameworks to detect unsafe or malicious inputs. A key focus is building scalable inference systems that can process billions of requests while maintaining low latency and high precision. The role also involves collaborating with Google DeepMind research teams to integrate cutting-edge defense techniques into production systems.

Additional responsibilities include designing observability tools for model behavior tracking, implementing automated red-teaming pipelines, and improving data quality for training robust classifiers. Strong expertise in Python, C++, distributed computing systems, and ML infrastructure is essential. This is a high-impact engineering role requiring both research literacy and production engineering excellence.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a Staff-level, elite-tier engineering role with significant barriers to entry. Candidates are expected to demonstrate deep expertise in ML systems, production-grade distributed architectures, and adversarial security. Competition is intensified by Google’s brand strength and the strategic importance of GenAI safety.

🚀 Career Impact

This role provides exceptional career acceleration in AI safety engineering, positioning engineers at the forefront of GenAI security research and production deployment. Experience gained here directly translates into senior leadership roles across top AI labs and hyperscale companies.

📋 Key Responsibilities

You will be responsible for designing and deploying AI safety classifiers, building LLM-based evaluation systems, and developing scalable infrastructure to detect and mitigate adversarial attacks. The role includes ownership of prompt injection detection pipelines, real-time monitoring systems, and automated safety scoring models.

You will work closely with DeepMind research teams to integrate experimental defense mechanisms into production systems. A significant part of the role involves building distributed data processing systems, optimizing inference performance, and ensuring system reliability under global-scale traffic.

Additionally, you will design tools for model observability, implement continuous evaluation frameworks, and improve dataset pipelines used for training safety-critical classifiers. The position requires balancing research innovation with production stability across large-scale GenAI systems.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

This section is personalized by seniority.

🧠 Fit & Positioning Analysis

Evaluate your match before applying.

📅 Application Signals

This role shows strong application urgency due to its placement in critical AI safety infrastructure for Google Workspace. Expect high competition from senior ML engineers globally, particularly from AI labs and hyperscalers. Interview cycles typically move within 2–4 weeks for strong candidates, with faster progression for those with direct GenAI safety experience.

Because this role supports production-facing LLM systems, hiring pipelines tend to prioritize candidates who demonstrate immediate impact potential and system ownership capability.

🔗 Apply for this Job

Apply on Company Site

✅ Job Source & Verification

This job post is based on official Google Careers listing data and structured role information provided for Staff-level AI/ML engineering positions. Source credibility: High (direct enterprise listing). Last updated: June 16, 2026. Details reflect verified compensation bands, responsibilities, and role scope typical of Google’s GenAI Safety and Security engineering organization.