About Nominal

Nominal is a venture-backed company with offices in Los Angeles, Austin, and New York City that specializes in software and data management products for organizations that are testing and validating complex physical systems (like drones, planes, rockets, engines, satellites, nuclear reactors, etc.). We are backed by prolific and experienced venture capital firms like General Catalyst, Lux Capital, Founders Fund, XYZ, Haystack, Human Capital, BoxGroup, etc., and have raised significant venture funding with strong early traction in both commercial and defense applications.

The Nominal team comes from commercial companies like SpaceX, Palantir, Anduril, Lockheed Martin, and NASA and is active amongst customers in aerospace, defense, industrial, and advanced energy applications (autonomous aviation, eVTOL/VTOL, flight testing, satellite development, etc.). We are also building and delivering solutions to the United States Air Force (USAF) who are looking to expand use cases across the broader DoD test community.

Our product is a data visualization and computation platform designed to accelerate how engineering teams test and validate hardware systems. We specifically aim to shorten the data review process after running tests and help engineering organizations scale testing campaigns more efficiently and effectively to save time and lower costs. It works by combining heterogeneous data into runs and allowing users to easily build custom visualization and analysis. Users write test logic with interactive computation, and these checks can be applied to historical and future runs to compound learnings. Data sources can include telemetry, sensor data, logs, simulations, and other testing metadata like environment, vehicle, part, version, etc.

• Develop Nominal's open-source Python client into a world-class DevUX for working with machine-derived test data
• Assist with technical pre-sales collateral such as end-to-end customer demos, documentation, and blog posts
• Simulate, ingest, munge, and visualize a broad set of real-world test data, including telemetry logs and video files

• Demonstrated experience developing or contributing to ergonomic Python libraries with great DevUX
• Demonstrated experience creating or troubleshooting REST API services
• Opinionated data science experience with standard Python tooling: NumPy, Pandas, OpenCV, etc
• Object-oriented design expertise with latest Python best-practices (>3.11)

• Experience contributing to open-source Python projects
• Background in hardware troubleshooting: from experimental physicist to Arduino tinkerer
• Knowledge and excitement about the emerging "software for hardware" startup space
• Passion for quality documentation and delightful DevUX

• Medical, dental, and vision insurance with 100% of premiums covered
• Unlimited PTO /sick leave
• Free lunch, snacks, and coffee
• Professional development stipend
• Quarterly company retreats

Don’t meet every single requirement? If you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway!