Job Description

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 test and validate complex physical systems (like drones, planes, rockets, engines, satellites, nuclear reactors, etc.). We are backed by prolific and experienced venture capital firms like Founders Fund, Lux Capital, XYZ, Haystack, Human Capital, BoxGroup, etc., and have raised significant venture funding with strong early traction in both commercial aerospace as well as defense applications with the Department of Defense (DoD). 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) and 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 include telemetry, sensor data, logs, simulations, and other testing metadata like environment, vehicle, part, version, etc. About the role Quickly drive projects end-to-end, after a period of mentorship from our world-class team Learn about the cutting-edge data infrastructure, considering high frequency, high volume, streaming data with transformation and alerting capabilities Experience life at an early-stage company! Watch Nominal as it grows the team, engages with new customers, and rapidly expands its product offering We’d love to hear from you if… You are targeting full-time work starting in Summer 2024 You are an eager, curious learner and (with the help of teammates) able to run through walls You have experience working with infrastructure for high-scale distributed systems or complex internal tools You have excitement to be a foundational member of the early team building software tools to amplify the capabilities of remarkable hardware engineering teams You have an interest in occasionally traveling to spend time with end-users on-site (e.g. rocket test stands, spacecraft clean rooms, automated manufacturing facilities), and to co-locate periodically with your teammates Skills that supercharge us Relevant data technologies: Apache Arrow, DataFusion, Flink, Beam, Kafka, D3.js , Superset, DuckDB, Plotly.js , TimescaleDB, QuestDB, Druid, Parquet, InfluxDB Modern technologies: Typescript, Next.js , tRPC, Java, Wasm, WebGL, ZeroMQ, serverless functions, React, Postgres DevOps tools and infrastructure: AWS, K8s, EKS, Helm, FluxCD Benefits/Perks Medical, dental, and vision insurance with 100% of premiums covered Unlimited PTO/sick leave Free lunch, snacks, and coffee Learning stipend Quarterly company retreats $115,000 - $130,000 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 Nominal, Inc

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