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Aurora builds autonomous driving systems for commercial freight, with the Aurora Driver designed to operate long-haul trucks in partnership with OEMs and logistics carriers. The tech stack—C++, Python, PyTorch, TensorFlow, CUDA, LiDAR, plus cloud infrastructure (AWS, GCP, Azure)—reflects a mature autonomous-systems org running distributed ML training pipelines and real-time vehicle control. Security and infrastructure hiring (17 security roles, 12 ops roles) signals scaling pressures around secure autonomous-vehicle design and fleet operations at production scale.
Tech Stack 167 technologies
Core StackSolidWorks CATIA C++ Python AWS PyTorch Jira Confluence Slack Go Kubernetes gRPC TensorFlow Terraform Keyshot LiDAR UNIX POSIX Protocol Buffers Parquet HDFS GCP Azure Opsgenie MapReduce RTOS TCP/IP CUDA TensorRT Bazel+133 more
What Aurora Is Building
◆Challenges
- Scaling fleet operations
- Partner api integration
- Identifying talent gaps
- Complex product integration
- Cost-effective supply
- Secure design for autonomous vehicle platform
- Improving performance review system
- Improving assurance levels of security across products
- Ensuring secure design of autonomous vehicle software
- Improving safety of autonomous vehicle
▲Active Projects
- Apqp and ppap process management
- Prototype to production supply chain
- Performance review cycle refinement
- Core security infrastructure services (certificate management, secrets management, authentication/authorization)
- Federation/sso solution
- Model training pipelines
- Autonomous vehicle fleet management solutions
- Optimizing the aurora driver architecture for our scale-generation vehicle platform and aurora driver hardware kit
- Security framework development for autonomous vehicle platform
- Aurora atlas mapping storage and versioning system
Hiring Activity
150 roles · 65 in 30d
Department
Seniority
Notable leadership hires: Backend Tech Lead, Technical Lead Manager, 3D Technical Director
Company intelligence