Nominal, Inc
Software Engineer, Python Applications
Nominal, Inc, Austin, Texas, us, 78716
About NominalNominal 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.
About the roleDevelop Nominal's open-source Python client into a world-class DevUX for working with machine-derived test dataAssist with technical pre-sales collateral such as end-to-end customer demos, documentation, and blog postsSimulate, ingest, munge, and visualize a broad set of real-world test data, including telemetry logs and video filesWe're looking for someone withDemonstrated experience developing or contributing to ergonomic Python libraries with great DevUXDemonstrated experience creating or troubleshooting REST API servicesOpinionated data science experience with standard Python tooling: NumPy, Pandas, OpenCV, etc.Object-oriented design expertise with latest Python best-practices (3.11)Skills that supercharge usExperience contributing to open-source Python projectsBackground in hardware troubleshooting: from experimental physicist to Arduino tinkererKnowledge and excitement about the emerging "software for hardware" startup spacePassion for quality documentation and delightful DevUXBenefits/PerksMedical, dental, and vision insurance with 100% of premiums coveredUnlimited PTO /sick leaveFree lunch, snacks, and coffeeProfessional development stipendQuarterly company retreats
$90,000 - $150,000 a year
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offers may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in all offers and are considered part of Nominal’s total compensation package.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!
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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.
About the roleDevelop Nominal's open-source Python client into a world-class DevUX for working with machine-derived test dataAssist with technical pre-sales collateral such as end-to-end customer demos, documentation, and blog postsSimulate, ingest, munge, and visualize a broad set of real-world test data, including telemetry logs and video filesWe're looking for someone withDemonstrated experience developing or contributing to ergonomic Python libraries with great DevUXDemonstrated experience creating or troubleshooting REST API servicesOpinionated data science experience with standard Python tooling: NumPy, Pandas, OpenCV, etc.Object-oriented design expertise with latest Python best-practices (3.11)Skills that supercharge usExperience contributing to open-source Python projectsBackground in hardware troubleshooting: from experimental physicist to Arduino tinkererKnowledge and excitement about the emerging "software for hardware" startup spacePassion for quality documentation and delightful DevUXBenefits/PerksMedical, dental, and vision insurance with 100% of premiums coveredUnlimited PTO /sick leaveFree lunch, snacks, and coffeeProfessional development stipendQuarterly company retreats
$90,000 - $150,000 a year
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offers may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in all offers and are considered part of Nominal’s total compensation package.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!
#J-18808-Ljbffr