Job description

WE ARE LOOKING FOR THE BEST ABOUT US 42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles. We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system. ABOUT THE ROLE 42dot’s Autonomy organization is seeking a Cloud Infrastructure Engineer to build and operate the cloud infrastructure that powers our autonomous driving data and ML workloads. You will work across AWS, Kubernetes, and cloud data platforms to enable reliable, scalable, and efficient development and production environments. Partnering closely with the Data, and ML Platform teams, you will establish reusable infrastructure patterns and apply DataOps and MLOps best practices to accelerate the development and deployment of next-generation autonomous driving technologies. Responsibilities - Lead, build, test, and release complex infrastructure services for the autonomy organization on AWS. - Drive upgrades and improvements to our Kubernetes infrastructure and build developer-facing tooling that improves development velocity. - Set up fault-tolerant, multi-region environments for data operations and data applications. - Own CI/CD pipelines for application and data projects. - Define the on-call strategy, participate in on-call rotations, and drive root-cause analysis of production incidents. - Build automated workflows and developer tooling so the Data, and ML Platform teams can deploy and operate services with less manual work. - Build and optimize highly reliable, scalable, and distributed infrastructure using a microservice architecture. - Collaborate with security and privacy to perform audits and mitigate findings. Qualifications - Bachelor's degree or higher in Computer Science, Engineering, or a similar technical field. - Minimum of 5 years of experience in software engineering, cloud infrastructure, or ML/Dev/Data Ops. - Production experience with Kubernetes and core cloud services across compute, storage, networking, identity, and secrets (AWS, Amazon EKS). - Hands-on experience with infrastructure as code and configuration management (Terraform, Pulumi, CloudFormation, or CDK). - Experience monitoring production systems and performing root-cause analysis (Datadog, Prometheus, or CloudWatch). - Proficient in Python or Go, with hands-on experience using Git-based tooling for automation. - Experience with CI/CD and GitOps (GitLab, Argo CD, or similar). Preferred Qualifications - Deep understanding of Kubernetes internals, and ecosystem tooling such as Helm. - Experience with observability, including metrics and distributed tracing. - Experience with GPU or ML platform workloads. - Linux internals, networking, and distributed systems. - Experience at an autonomous-driving, or robotics company. - Understanding of data governance, data privacy, and security controls for cloud infrastructure. Interview Process - Application Review - Coding Test - 1st interview - 2nd interview - Offer Negotiation - Hiring - The screening procedures may vary depending on the position, schedule, or other circumstances. You will be individually notified of the screening schedule and results via the email address provided in your application. Compensation - $145,000 - $240,000 Additional Information - In accordance with fair hiring practices, do not include any personal information unrelated to your job qualifications (e.g., Social Security Number, family relations, marital status, age, photo, physical condition, place of birth, etc.) in your resume. - All documents must be submitted in PDF format and under 30MB in size. - If you experience issues uploading your resume, please send it along with the job posting URL to recruit@42dot.ai. - We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws. - Qualified individuals with disabilities are encouraged to apply and will receive consideration under the Americans with Disabilities Act (ADA). - 42dot does not accept unsolicited resumes and will not pay fees for any such submissions. Equal Opportunity Statement - 42dot is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status. ※ Please review the following information before applying. - How to work in 42dot, About 42dot Way → 42dot.ai

Requirements

Must-haves

Lead, build, test, and release complex infrastructure services for the autonomy organization on AWS.
Drive upgrades and improvements to our Kubernetes infrastructure and build developer-facing tooling that improves development velocity.
Set up fault-tolerant, multi-region environments for data operations and data applications.
Own CI/CD pipelines for application and data projects.
Define the on-call strategy, participate in on-call rotations, and drive root-cause analysis of production incidents.
Build automated workflows and developer tooling so the Data, and ML Platform teams can deploy and operate services with less manual work.
Build and optimize highly reliable, scalable, and distributed infrastructure using a microservice architecture.
Collaborate with security and privacy to perform audits and mitigate findings.
Bachelor's degree or higher in Computer Science, Engineering, or a similar technical field.
Minimum of 5 years of experience in software engineering, cloud infrastructure, or ML/Dev/Data Ops.
Production experience with Kubernetes and core cloud services across compute, storage, networking, identity, and secrets (AWS, Amazon EKS).
Hands-on experience with infrastructure as code and configuration management (Terraform, Pulumi, CloudFormation, or CDK).
Experience monitoring production systems and performing root-cause analysis (Datadog, Prometheus, or CloudWatch).
Proficient in Python or Go, with hands-on experience using Git-based tooling for automation.
Experience with CI/CD and GitOps (GitLab, Argo CD, or similar).

Nice-to-haves

Deep understanding of Kubernetes internals, and ecosystem tooling such as Helm.
Experience with observability, including metrics and distributed tracing.
Experience with GPU or ML platform workloads.
Linux internals, networking, and distributed systems.
Experience at an autonomous-driving, or robotics company.
Understanding of data governance, data privacy, and security controls for cloud infrastructure.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlawskubernetesci/cdpythongo

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Vision