Senior SRE for AI Platform Reliability & MLOps

Tiger Analytics; Washington (District of Columbia); Hybrid; USD 110,000 - 160,000; Full time

Job summary

Tiger Analytics is seeking a Site Reliability Engineer (SRE) in Washington, DC to ensure the resilience and performance of data-driven AI platforms. The role involves a blend of software engineering and systems architecture, focusing on MLOps to maintain high availability for AI models. Responsibilities include managing SLAs, Kubernetes scaling, and automating operations. Ideal candidates will have expertise in Kubernetes, Docker, and Python. Benefits include significant career development opportunities in a fast-growing environment.

Qualifications

• Expert-level knowledge of Kubernetes and Docker required.
• Strong proficiency in Python and Bash for automation.
• Familiarity with MLOps tools like Kubeflow or Vertex AI is needed.

Responsibilities

• Ensure production ecosystems are resilient, scalable, and performant.
• Define and maintain SLOs and SLIs for AI/ML services.
• Optimize resources for Large Language Models.

Skills

Kubernetes

Docker

Python

Bash

MLOps tools (Kubeflow, Vertex AI)

Data Systems management

Networking (VPCs, Load Balancers)

Tools

Terraform

Prometheus

Grafana

Google Cloud Operations Suite

Job description

Tiger Analytics is seeking a Site Reliability Engineer (SRE) in Washington, DC to ensure the resilience and performance of data-driven AI platforms. The role involves a blend of software engineering and systems architecture, focusing on MLOps to maintain high availability for AI models. Responsibilities include managing SLAs, Kubernetes scaling, and automating operations. Ideal candidates will have expertise in Kubernetes, Docker, and Python. Benefits include significant career development opportunities in a fast-growing environment.