Bachelor's degree in Computer Science, Engineering, or related field.
5+ years in software engineering, cloud infrastructure, or ML/Dev/Data Ops.
Production experience with Kubernetes and AWS core services.
Hands-on with infrastructure as code tools like Terraform or CloudFormation.
Experience in monitoring production systems and root-cause analysis.
Proficient in Python or Go, with Git-based automation experience.
Familiarity with CI/CD and GitOps methodologies.
Responsibilities
Lead the development and release of infrastructure services on AWS.
Enhance Kubernetes infrastructure and create developer tools.
Establish fault-tolerant, multi-region environments for data operations.
Manage CI/CD pipelines for applications and data projects.
Define and participate in on-call strategies and incident analysis.
Automate workflows for Data and ML Platform teams.
Design and optimize scalable, distributed infrastructure using microservices.
Benefits
Encouragement of applications from U.S. veterans and eligible candidates.
Support for fair hiring practices and diversity in the workplace.
Full Job Description
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.
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 [redacted].
We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws.
※ Please review the following information before applying.
