Scout Motors
AI Infrastructure Engineer
About this role
Scout Motors seeks an AI Infrastructure Engineer to build and maintain scalable infrastructure supporting machine learning and large language model workloads. You'll design cloud and on-premises deployments, manage CI/CD pipelines, and ensure reliability of AI systems across the organization.
What you'll do
- Install, configure, and maintain AI platforms, tools, and infrastructure supporting ML/LLM workloads
- Design, build, and deploy containerized AI services using Docker across cloud and on-prem environments
- Develop and maintain ML CI/CD pipelines for model training, testing, and production deployment
- Automate infrastructure provisioning with Terraform and Infrastructure-as-Code best practices
- Monitor system performance, implement observability for agentic AI systems, and ensure reliability and debuggability
- Perform security updates, patching, access control, and vulnerability remediation for AI platforms
What they're looking for
- LLM platforms, LLMOps, and MLOps (8+ years)
- Terraform and Infrastructure-as-Code
- Docker containerization and image optimization
- AWS cloud platform expertise
- CI/CD tooling (GitHub Actions, GitLab CI)
- Kubernetes and container orchestration
- Python, PySpark, and Bash scripting
- Security best practices and patch management
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Scout Motors
Scout Motors develops next-generation electric and extended-range electric pickup trucks and SUVs with authentic off-road performance. The company is hiring engineers across powertrains, body structures, electronics, and audio systems to design and integrate these vehicles from concept through production.
- Website
- scoutmotors.com
Likely interview questions
- Walk us through your experience designing and deploying ML infrastructure in production—what were the key challenges and how did you address them?
- Describe your approach to building and maintaining CI/CD pipelines for machine learning models. What tools have you used and why?