Senior Machine Learning Infrastructure Engineer

Unity is looking for a Senior Machine Learning Infrastructure Engineer to join their Vector Ads team, where they build the real-time systems that power Unity's global advertising platform. The role involves building and operating the infrastructure that brings ML models from training into production, ensuring the systems run reliably at scale.

Responsibilities:

• Design, build, and maintain the infrastructure that serves ML models in real-time across Unity's ads ecosystem
• Build and operate scalable model serving pipelines — owning latency, throughput, and reliability in a high-QPS production environment
• Partner with ML engineers to productionize models, manage model deployments, and improve iteration speed
• Improve observability, performance, and cost-efficiency of ML serving infrastructure
• Contribute to architectural decisions around feature serving, model versioning, and inference optimization

Requirements:

• Experience building and operating ML infrastructure or model serving systems in production
• Proficiency in Golang or Python, with strong systems engineering fundamentals
• Hands-on experience with Kubernetes and container orchestration at scale
• Familiarity with ML serving frameworks such as Ray Serve, Triton, TorchServe, or similar
• Understanding of distributed systems, API design, and system reliability
• Strong collaboration and communication skills in a remote-first environment
• Experience with feature stores, feature pipelines, or online/offline feature serving
• Background in ad tech, real-time bidding, or programmatic advertising systems
• Familiarity with infrastructure-as-code such as Terraform
• Experience with observability tooling — Prometheus, Grafana, OpenTelemetry
• Background with real-time data pipelines, caching layers, or low-latency serving systems