Software Engineer - Production - #2084278
Applied Intuition
Date: vor 14 Stunden
Stadt: München
Vertragstyp: Ganztags
Arbeitsplan: Volle Tag

About Applied Intuition
Applied Intuition is a vehicle software supplier that accelerates the adoption of safe and intelligent machines worldwide. Founded in 2017, Applied Intuition delivers the AI-powered ADAS/AD toolchain, Vehicle OS, and autonomy stack to help customers shorten time to market, build high-quality systems, and create next-generation consumer experiences. 18 of the top 20 global automakers trust Applied Intuition’s solutions to drive the production of modern vehicles. Applied Intuition serves the automotive, trucking, construction, mining, agriculture, and defense industries and is headquartered in Mountain View, CA, with offices in San Diego, CA, Ft. Walton Beach, FL, Ann Arbor and Detroit, MI, Washington, D.C., Stuttgart, Munich, Stockholm, Seoul, and Tokyo. Learn more at appliedintuition.com.
We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. (Note: this is not applicable for EpiSci roles).
About The Role
Modern autonomous system development is heavily reliant on daily, realistic, and large scale simulations to test constant software changes. Join our cloud platform team to ensure we're building efficient and reliable systems for managing these large-scale workloads.
As a production engineer you'll be improving the development and deployment of our large-scale simulation infrastructure. The compute and data generation scale of our product workloads pushes the boundaries of standard cluster deployments, and you'll be at the forefront of helping build out and ensure reliability of this system. All while ensuring the deployment infrastructure is interoperable with various custom autonomy software and infrastructure used across the world.
You will work closely across the entirety of the engineering team to ensure the operational success of our backend and a variety of customer deployments. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, interact closely with users to collect feedback, and contribute to a thoughtful, dynamic team culture.
At Applied Intuition, you will:
Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.
Applied Intuition is a vehicle software supplier that accelerates the adoption of safe and intelligent machines worldwide. Founded in 2017, Applied Intuition delivers the AI-powered ADAS/AD toolchain, Vehicle OS, and autonomy stack to help customers shorten time to market, build high-quality systems, and create next-generation consumer experiences. 18 of the top 20 global automakers trust Applied Intuition’s solutions to drive the production of modern vehicles. Applied Intuition serves the automotive, trucking, construction, mining, agriculture, and defense industries and is headquartered in Mountain View, CA, with offices in San Diego, CA, Ft. Walton Beach, FL, Ann Arbor and Detroit, MI, Washington, D.C., Stuttgart, Munich, Stockholm, Seoul, and Tokyo. Learn more at appliedintuition.com.
We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. (Note: this is not applicable for EpiSci roles).
About The Role
Modern autonomous system development is heavily reliant on daily, realistic, and large scale simulations to test constant software changes. Join our cloud platform team to ensure we're building efficient and reliable systems for managing these large-scale workloads.
As a production engineer you'll be improving the development and deployment of our large-scale simulation infrastructure. The compute and data generation scale of our product workloads pushes the boundaries of standard cluster deployments, and you'll be at the forefront of helping build out and ensure reliability of this system. All while ensuring the deployment infrastructure is interoperable with various custom autonomy software and infrastructure used across the world.
You will work closely across the entirety of the engineering team to ensure the operational success of our backend and a variety of customer deployments. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, interact closely with users to collect feedback, and contribute to a thoughtful, dynamic team culture.
At Applied Intuition, you will:
- Create and implement best practices for deploying and maintaining software for multiple customers across all three major cloud providers (AWS, GCP, Azure) with minimal downtime and high reliability
- Monitor Applied Intuition's software on deployed machines and architect solutions to any bottlenecks that are encountered
- Improve developer efficiency by building internal tooling and optimizing our CI/CD systems
- 5+ years of experience in a software engineering role working on infrastructure, monitoring, or a large scale software product
- 5+ years of coding experience from shell scripting (e.g., Bash) to higher-level languages (e.g., Python)
- Experience with microservice orchestration frameworks such as Kubernetes
- Experience working with containerized systems (e.g., Docker)
- Experience utilizing open source tooling
- Experience with deploying software on either public clouds (e.g., AWS) or on-premise clusters
Applied Intuition is an equal opportunity employer and federal contractor or subcontractor. Consequently, the parties agree that, as applicable, they will abide by the requirements of 41 CFR 60-1.4(a), 41 CFR 60-300.5(a) and 41 CFR 60-741.5(a) and that these laws are incorporated herein by reference. These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, sexual orientation, gender identity or national origin. These regulations require that covered prime contractors and subcontractors take affirmative action to employ and advance in employment individuals without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability. The parties also agree that, as applicable, they will abide by the requirements of Executive Order 13496 (29 CFR Part 471, Appendix A to Subpart A), relating to the notice of employee rights under federal labor laws.
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