Ground Software Engineer Intern at Millennium Space Systems focusing on software development, integration, and testing for satellite systems. Collaborating with engineers and technicians to ensure software quality and functionality.
About the role
- Senior Full-Stack Software Engineer developing a platform for configuring autonomous driving scenarios. Focusing on scalable web services and cloud deployment practices.
Responsibilities
- Lead the hands-on development of the platform's user interface
- Build, develop, and deliver high-quality, full-stack features from concept through deployment
- Write clean, performant, and maintainable production code for both frontend interfaces and distributed backend services
- Implement and manage integrations with core APIs (gRPC and REST) and data infrastructure
- Help maintain and improve CI/CD pipelines in GitLab and Jenkins
- Support the deployment and upkeep of containerized services managed by Docker and Kubernetes/Helm
- Actively participate in the code review process
- Identify, debug, and resolve complex technical issues, performance bottlenecks, and operational incidents
- Work closely with the Tech Lead and multi-functional teams (ML Engineers, Product Managers)
Requirements
- Master's degree (M.S.), or a Bachelor's degree (B.S.) in Computer Science, Software Engineering, Electrical Engineering, or a closely related technical field (or equivalent experience)
- Minimum 10+ years of hands-on experience developing and deploying scalable full-stack web services in a production cloud environment
- Deep expertise and proven track record in a modern frontend framework (e.g., React, Vue, Angular)
- Mastery of TypeScript and JavaScript for robust client-side development and state management architecture
- Proven proficiency in developing backend systems that handle high volume and growth using Python and/or Go
- Hands-on experience implementing and consuming APIs built with Protocol Buffers
- Solid practical experience with containerization using Docker and exposure to orchestration tools like Kubernetes and Helm
- Experience with cloud services, particularly AWS S3, and familiarity with SQL for data management
- Demonstrated knowledge of CI/CD practices along with experience using source control platforms like GitLab
- Experience with MaaS (Model-as-a-Service) patterns and serving large machine learning models as high-throughput endpoints
Benefits
- eligible for equity
- benefits
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