Staff Engineer, ML/AI Platform
Core
Architect and build foundational ML/AI infrastructure enabling engineers and data scientists to train, deploy, and serve models and agentic systems at massive scale.
Role type
Staff Machine Learning Platform Engineer (MLOps/Infrastructure)
Builds
Production-grade ML serving layers, agentic stacks, data pipelines, and model lifecycle management systems.
Domain
AI/ML Infrastructure, Marketing Technology
Deliverable
production ML models | infrastructure
Required skills
ML Platform/MLOps architecture, Python (batch & online), Spark, Ray, MLFlow, Kubeflow, Metaflow, agentic stack design, real-time inference systems, champion/challenger testing, model lifecycle management
Preferred skills
Reinforcement learning, agentic infrastructure (MCP, context store, orchestration), low-latency high-volume workloads
Technologies
Ray, MLFlow, Metaflow, Argo, Spark, Kubernetes, EKS, Istio, Terraform, HuggingFace, PyTorch, TensorFlow, Pandas, AWS, DynamoDB, Aurora, AirFlow, Postgres, Redis, React, TypeScript, GraphQL
Responsibilities
Architect ML platform strategy spanning data pipelines, training infrastructure, and serving layers; Build and operate production-grade, low-latency ML serving layers with robust model lifecycle systems; Define and drive Attentive's agentic stack; Provide ML infrastructure perspective in high-level strategic discussions; Mentor platform and ML engineers; Build universal interfaces and architectures bridging platform capabilities with product needs
Seniority
Staff, high-impact individual contributor with technical leadership and mentorship
