Senior ML Infrastructure Engineer

Parametric builds autonomous physical businesses. As a Senior ML Infrastructure Engineer, you will design and manage the distributed infrastructure for robot learning, including orchestrating DAG workflows, provisioning compute clusters, building A/B experimentation platforms, enforcing data lineage, and optimizing training throughput.

• Orchestrate complex DAG workflows using Airflow, Argo, or Temporal.
• Architect parallelized compute clusters on Kubernetes/Slurm.
• Engineer A/B experimentation infrastructure for model comparison.
• Enforce end-to-end data lineage and provenance.
• Optimize training throughput by debugging distributed training loops.

• 3+ years in DevOps, ML infrastructure, or platform engineering.
• Expert-level AWS proficiency (EC2, Spot Fleets, S3).
• Experience with workflow orchestration (Temporal, Dagster, Airflow).
• Hands-on Kubernetes (EKS, Helm, Karpenter).
• Infrastructure as Code (Terraform, Pulumi, AWS CDK).
• CI/CD pipelines (GitHub Actions, Jenkins).
• Strong Python and Bash scripting.