At Relativity Space, we’re building rockets to serve today’s needs and tomorrow’s breakthroughs. Our Terran R vehicle will deliver customer payloads to orbit, meeting the growing demand for launch capacity. But that’s just the start. Achieving commercial success with Terran R will unlock new opportunities to advance science, exploration, and innovation, pioneering progress that reaches beyond the known.
Joining Relativity means becoming part of something where autonomy, ownership, and impact exist at every level. Here, you're not just executing tasks; you're solving problems that haven’t been solved before, helping develop a rocket, a factory, and a business from the ground up. Whether you’re in propulsion, manufacturing, software, avionics, or a corporate function, you’ll collaborate across teams, shape decisions, and see your work come to life in record time. Relativity is a place where creativity and technical rigor go hand in hand, and your voice will help define the stories we’re writing together. Now is a unique moment in time where it’s early enough to leave your mark on the product, the process, and the culture, but far enough along that Terran R is tangible and picking up momentum. The most meaningful work of your career is waiting. Join us.
About the Team:
Relativity Space is on a mission to better connect humanity to space and the universe beyond our planet. With decades of experience scaling world-class technology organizations like Google, CEO Eric Schmidt is guiding Relativity into its next phase: advancing Terran R toward launch and building the foundation for long-term impact.
The Data & AI organization at Relativity Space is a critical pillar supporting our work to build autonomous rocket factories and launch platforms. Our mission is to develop and integrate data engineering, machine learning, and AI technologies that provide actionable insights, automate decision-making, and drive efficiencies across our operations.
As a director, you’ll shape the strategies and technologies that power these systems. You will lead a cross-functional team focused on delivering high-performance data pipelines, building scalable AI models, and ensuring that AI-driven automation plays a central role in transforming operations from Earth to Mars
About the Role:
As the Director of Data & AI, you will be responsible for the strategic direction and technical leadership of our data and AI initiatives, which include:
- Data Engineering: Lead the design and implementation of scalable data architectures, including ETL pipelines, data modeling, data warehouse management, and reporting infrastructure, ensuring high-quality, actionable data across all systems.
- Data Platform: Oversee the development of a distributed data platform that supports mission-critical applications, enabling real-time data ingestion, access, and orchestration for test and launch and factory operations.
- Machine Learning & AI: Direct the design, development, and deployment of AI and machine learning models that leverage our data to drive automation, decision-making, and predictive analytics across the organization. Ensure these models are scalable, reliable, and move the needle on critical metrics for the company.
- Leadership & Mentorship: Lead, mentor, and grow a team of software engineers, data engineers and machine learning engineers. Create an environment that fosters innovation, continuous learning, and technical excellence while aligning goals with company objectives.
- Collaboration & Strategy: Partner with leadership and cross-functional users across the company to define the long-term strategy for data and AI initiatives, aligning the technical roadmap with company goals.
In this role, you will define the future of how Relativity Space uses data and AI to drive smarter, more efficient operations.
About You:
- Education: Degree in Computer Science.
- Experience: 10+ years of experience in software engineering, data engineering or machine learning, with at least 5 years in a leadership role, overseeing large-scale systems.
- AI & Machine Learning Expertise: Experience designing, building, and deploying AI models and machine learning systems, particularly in high-performance or mission-critical environments. Proficient in AI techniques including deep learning, reinforcement learning, and natural language processing.
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Foundational Machine Learning Knowledge: Understanding of core ML concepts. Experience with advanced models such as Transformers/LLMs, LSTM models, time-series forecasting, and predictive analytics for real-time decision-making and automation. Familiarity with the mathematical underpinnings of ML.
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AI Infrastructure Experience: Experience with building and scaling AI infrastructure, including deploying and managing machine learning models in production environments. Experience with agentic architectures (e.g., MCP).
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Data Engineering: Experience in building scalable data architectures, including ETL pipelines, data modeling, and analytics.
- Expertise with modern data tools and technologies (e.g., Kafka, Spark, SQL, NoSQL, data lakes).
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Cloud & Platform Development: Understanding of cloud platforms (AWS, GCP, etc.), containerization (Docker, Kubernetes), and orchestration for building and deploying services.