About the Role

As a Product Safety Engineer on the Imagine team, you will build critical safety systems and infrastructure for Grok’s multimodal generation capabilities. Your work will ensure that these capabilities are powerful and responsibly deployed, balancing innovation with rigorous safety and trustworthiness.

Responsibilities

Design and implement scalable safety systems for Grok’s media generation platform, including real-time content moderation, risk detection, and safeguard enforcement for images, video, and audio.
Build infrastructure to measure, monitor, and mitigate safety risks such as harmful content, bias, deepfakes, intellectual property issues, and misuse at global scale.
Develop tools, pipelines, and evaluation frameworks that enable rapid iteration on safety policies in collaboration with researchers, product, and policy teams.
Architect robust feedback loops between user interactions, model outputs, and training data to continuously improve safety while maintaining high performance and low latency.
Own full-cycle development of safety features: from problem definition and prototyping to deployment, monitoring, incident response, and long-term refinement.
Partner closely with the Imagine engineering, research, and product teams to embed safety into core features and deliver delightful yet responsible user experiences.

Basic Qualifications

Proficiency in Rust, with a strong track record of writing clean, efficient, maintainable, and scalable code.
Experience designing and building production safety, trust & safety, or content moderation systems for consumer-facing products at scale.
Hands-on expertise developing real-time detection systems, data pipelines, or evaluation frameworks for high-throughput AI applications.
Proven ability to deliver robust, reliable solutions that reach millions of users while maintaining high standards of uptime and performance.
Strong problem-solving skills and a passion for turning complex safety challenges into practical, high-impact engineering solutions.
Deep enthusiasm for responsible AI development and a commitment to building systems that advance humanity’s understanding while protecting users.

Preferred Skills and Experience

Experience with multimodal content safety (images, video, audio) or generative AI safety in production environments.
Familiarity with machine learning classifiers, safety evaluation, red-teaming, or adversarial testing for media generation models.
Background in distributed systems, real-time inference serving, Kubernetes, observability tools, or large-scale data infrastructure.

Requirements

Proficiency in Rust

You should have a strong track record of writing clean, efficient, maintainable, and scalable code.

Experience in safety systems

You need to have experience designing and building production safety or content moderation systems for consumer-facing products.

Real-time detection systems

Hands-on expertise in developing real-time detection systems or data pipelines for high-throughput AI applications is required.

Problem-solving skills

Strong problem-solving skills and a passion for addressing complex safety challenges are essential.

Nice to Have

Multimodal content safety

Experience with multimodal content safety or generative AI safety in production environments is preferred.

Machine learning familiarity

Familiarity with machine learning classifiers and safety evaluation techniques is a plus.

Distributed systems background

A background in distributed systems and real-time inference serving would be beneficial.

Benefits

Impactful work

You will have the opportunity to make a lasting impact at the frontier of multimodal AI.

Collaborative environment

Work in a small, highly motivated team focused on engineering excellence.