Unity Technologies

Gaming

Développeuseoudéveloppeurcôtéserveur(backend)StaffSystèmesd’inférenceML/StaffBackendEngineer,MLInferenceSystems

Mountain View, California, United States
The Brief

“Développeuse ou développeur côté serveur (backend) Staff — Systèmes d’inférence ML / Staff Backend Engineer, ML Inference Systems at Unity Technologies. Skills: Backend services, Distributed systems, ML inference, Golang, GCP, Kubernetes, Prometheus, Grafana. Design, develop, and deploy production-grade backend services and distributed systems. Power large-scale online model inference at billions of daily requests”

Industry & Context.

Gaming

What They're Looking For.

Must Have

5+ years designing, deploying, and maintaining distributed systems at scale, Expertise in Golang for building high-performance, low-latency backend infrastructure, Hands-on experience with cloud infrastructure on GCP and workload orchestration with Kubernetes, Grounding in monitoring and observability tooling, including Prometheus and Grafana, Familiarity with microservice architectures, containerization (Docker), and CI/CD best practices, Familiarity with machine learning platforms, workflows, and serving infrastructure, Sufficient knowledge of English for professional verbal and written exchanges

Nice to Have

Experience in ad tech, recommender systems, real-time personalization, or other performance-critical domains, Experience with ML inference servers like NVIDIA Triton Inference Server, Familiarity with auction mechanics or bidding systems in an ad tech context

What You'll Do.

and deploy production-grade backend services and distributed systems

Power large-scale online model inference at billions of daily requests

Drive technical direction of our inference platform

high-throughput serving infrastructure

Ensure online serving infrastructure scales with growing model complexity and inference volumes

and efficiency of systems in production

Manage and optimize cloud infrastructure on GCP

Orchestrate workloads with Kubernetes

Promote and implement best practices for backend service development

How You'll Work.

Team & Collaboration

Collaborate with ML engineers to ensure online serving infrastructure scales with growing model complexity and inference volumes

Communication Scope

Professional verbal and written exchanges in English

Free ATS check

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