MLOps Engineer
Core
Build and operate MLOps platforms on AWS to support autonomous driving ML workloads, ensuring reproducible, traceable, and auditable ML workflows for automotive safety systems.
Role type
MLOps Engineer (Autonomous Driving)
Builds
Highly available, multi-zone training and deployment environments for ML models
Domain
Automotive / Autonomous Driving / Cloud Infrastructure
Deliverable
infrastructure
Required skills
AWS for ML workloads, Multi-GPU/distributed training (Ray), Kubernetes/EKS, Infrastructure as Code (Terraform), Apache Airflow, MLflow, Python for automation, CI/CD pipelines (GitHub)
Technologies
AWS, Ray, Kubernetes, EKS, Terraform, Apache Airflow, MLflow, GitHub Actions
Responsibilities
Build and operate MLOps platforms on AWS; Implement and maintain highly available, multi-zone training and deployment environments; Operate distributed, multi-GPU training setups; Troubleshoot and resolve platform-level issues impacting ML productivity; Implement and maintain ML pipelines for orchestration, experiment tracking, and model versioning; Support CI/CD pipelines for ML code, models, and infrastructure
Seniority
Mid-Senior, hands-on IC