Senior Software Development Engineer
Core
Design and implement robust, scalable cloud infrastructure for deploying video AI models and services, enabling ML engineers to rapidly iterate and deploy state-of-the-art video understanding models at massive scale.
Role type
Senior IC DevOps/Infrastructure Engineer (AI/ML workloads)
Builds
Kubernetes clusters, containerized deployment pipelines, MLOps pipelines, and observability systems for GPU-accelerated video AI
Domain
Media & Entertainment / Cloud Infrastructure / AI/ML Systems
Deliverable
infrastructure
Required skills
Kubernetes, container orchestration, cloud platforms (AWS/GCP/Azure), Python/Go, distributed systems, GPU infrastructure, MLOps tools, infrastructure-as-code, CI/CD, observability
Preferred skills
Database and storage systems optimization for large-scale workloads
Technologies
Docker, Kubernetes, Terraform, CloudFormation, Helm, Kubeflow, MLflow, Ray, Prometheus, ELK, Datadog, CUDA
Responsibilities
Design and implement robust, scalable cloud infrastructure for deploying video AI models and services; Build and maintain Kubernetes clusters and containerized deployment pipelines optimized for GPU workloads; Establish monitoring, logging, and observability systems for AI/ML production services; Develop infrastructure-as-code practices and automation for rapid, reliable deployment; Optimize cloud costs while maintaining performance and reliability standards; Work with ML engineers to develop efficient MLOps pipelines for model training, evaluation, and serving; Establish and maintain security, compliance, and data governance practices for AI systems; Mentor engineering teams on infrastructure best practices and cloud architecture patterns; Drive incident response, postmortems, and continuous improvement of system reliability
Seniority
Senior, hands-on IC