Member of Technical Staff - Imagine Safety

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.

SpaceXSI is building Super Intelligence to understand the universe and help expand humanity’s knowledge and capabilities. We work across the full Super Intelligence stack: compute (Colossus supercomputers), models (Grok), and applications (Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X). We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

ABOUT THE ROLE:

The Imagine team is redefining AI-driven media experiences for Grok users worldwide. As a Product Safety Engineer on the Imagine team, you will build the critical safety systems and infrastructure that ensure Grok’s multimodal generation capabilities (images, video, audio, and beyond) are powerful, delightful, and responsibly deployed. You’ll design and scale safeguards, detection systems, and evaluation frameworks that prevent harm while preserving creativity and user freedom.

Your work will directly shape how millions of users experience generative media — balancing rapid innovation with rigorous safety, trustworthiness, and alignment with SpaceXSI's mission.

If you’re a driven engineer passionate about AI safety, content integrity, and building robust systems that protect users without stifling innovation, this is your opportunity to make a lasting impact at the frontier of multimodal AI.

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.
• Track record collaborating across engineering, research, and policy teams to ship safety-critical features quickly and effectively.
• Previous work on content moderation, anti-abuse, model alignment, or responsible AI at consumer AI products.