Hadrian - Manufacturing the Future

Hadrian is building autonomous factories to reindustrialize America. By combining AI, advanced software, robotics, and full-stack manufacturing, we help aerospace and defense companies build rockets, satellites, aircraft, ships, and other mission-critical systems up to 10x faster and at significantly lower cost.

Following our $1.37B Series D at a $7.87B valuation, Hadrian is rapidly expanding our manufacturing footprint, launching new capabilities across welding, casting, forging, electronics, additive manufacturing, and more, while scaling our Factory-as-a-Service platform to transform how critical products are built.

Backed by leading investors including JPMorgan Chase, Valor Equity Partners, Andreessen Horowitz, Founders Fund, 137 Ventures, Lux Capital, T. Rowe Price, and Morgan Stanley, we’re building the future of American manufacturing—and looking for exceptional people to help make it happen.

If you’re ready to take on the most challenging and rewarding work of your career while helping create American manufacturing jobs for generations to come, you’re exactly who we’re looking for.

The Role

Hadrian is looking for a Data Science/ Data Engineer Intern to join the team building the data backbone of our autonomous factory. Every machine, part, and process on our floor generates data, and how well we move, model, and interpret that data determines how fast we can scale. You'll work alongside experienced engineers and analysts on real production data- from the pipelines that move machine telemetry and quality records into our warehouse to the models and analyses that shape how we run the factory. This is a hands-on role where your work will ship, and your contributions will directly influence operational decisions at Hadrian.

What You'll Do

Build and maintain data pipelines that move machine, production, quality, and program data from the factory floor into our warehouse

Model and structure datasets that engineering, operations, and quality teams rely on for daily decision-making

Analyze production data to surface insights on throughput, capacity, cycle time, yield, and machine utilization

Develop dashboards, metrics, and reporting that improve visibility into factory performance and program status

Prototype statistical or machine learning approaches for problems like anomaly detection, demand forecasting, or process optimization

Collaborate with cross-functional teams including operations, program management, and quality to translate open questions into measurable analyses

Write clean, well-tested, well-documented code and participate in code reviews

Surface data quality issues and contribute to discussions on how we instrument and govern our data

What We're Looking For

Current university student pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Math, Engineering, or a related field, with an expected graduation date between December 2027 and June 2028

Proficiency in Python and SQL

Familiarity with data pipelines, ETL/ELT workflows, or cloud data warehouses

Working knowledge of statistics and the ability to turn a messy dataset into a defensible conclusion

Strong problem-solving skills and the ability to work through ambiguous technical challenges

Clear written and verbal communication, including the ability to explain analysis to non-technical partners

Strong attention to detail and follow-through

Comfortable working in a fast-moving, highly ambiguous environment

Willingness to work on-site in Los Angeles, CA

Internships are available for our Fall 2026, Spring 2027, and Summer 2027 cohorts. Indicate your preferred term(s) when applying.

What Will Set You Apart

Prior internship or project experience building production data pipelines or shipping analysis that changed a decision

Experience with orchestration or transformation tooling

Exposure to time-series, sensor, or telemetry data

Interest in manufacturing systems, automation, or industrial software

What You'll Gain

Hands-on experience building data infrastructure and analysis for a high-growth, mission-driven industrial company