Senior ML Infrastructure Engineer
Core
Build the platform enabling ML engineers to rapidly iterate, experiment, and ship models, spanning feature pipelines, training infrastructure, evaluation, deployment, and monitoring.
Role type
Senior ML Infrastructure Engineer
Builds
Unified ML platform including CLI, SDK, compute orchestration, feature store, model registry, and model serving
Domain
Commercial HVAC/electrical/plumbing supply chain technology
Deliverable
production ML models
Required skills
Python, cloud infrastructure (AWS), infrastructure-as-code (Terraform/AWS CDK/Pulumi), managed ML inference/serving (SageMaker/Vertex AI), model registry management, API/SDK design, ML workflow understanding
Preferred skills
ML tooling integration (W&B/MLflow), workflow orchestration (Temporal/Prefect/Airflow), internal developer portal design, GPU compute providers, hands-on ML model training/deployment
Technologies
Python, AWS, Terraform, AWS CDK, Pulumi, SageMaker, Vertex AI, W&B, MLflow, Temporal, Prefect, Airflow
Responsibilities
Design and build CLI, SDK, and services as the single front door to the ML platform; Wire together cloud and SaaS stack into a unified system using infrastructure-as-code; Build cost attribution, usage dashboards, and monitoring for production model serving; Collaborate with ML engineers to transform one-off scripts into self-serve platform features
Seniority
Senior, hands-on IC
