Find jobs
Pricing
Free Resume Checker
Sign in
Sign up
FIND JOBSPRICINGFREE RESUME CHECKERSIGN INSIGN UP
Jobs
/DevOps Engineer jobs
Tiger Analytics Inc.

Sr. Site Reliability Engineer

SalaryNo pay range posted
LocationWashington, District of Columbia, United States
Work modehybrid
Typefull-time
SenioritySenior
DepartmentData Engineering
Company size5,001–10,000 people
First seenOct 5, 2026 · 6d ago
Verified live1d ago
District of Columbia law requires most employers to post a pay range.
At a glanceSummarised by Seekless from the posting.
Must have4
Expert-level knowledge of Kubernetes (K8s) and Docker
Strong proficiency in Python (for automation) and Bash
Experience managing the reliability of data-heavy services (BigQuery, Pub/Sub, or Vector Databases like Pinecone/Milvus)
Solid understanding of VPCs, Load Balancers, DNS, and secure service mesh (Istio/Anthos)
Nice to have2
Familiarity with MLOps tools such as Kubeflow, Vertex AI, MLflow, or DVC
Knowledge of Go is a plus
Skills
Kubernetes
Docker
Kubeflow
Vertex AI
MLflow
DVC
Python
Bash
Go
Terraform
Pulumi
GitHub Actions
Cloud Build
ArgoCD
Prometheus
Grafana
Google Cloud Operations Suite
BigQuery
Pub/Sub
Pinecone
Milvus
Istio
Anthos
GKE
Role Overview
We are seeking a high-caliber Site Reliability Engineer (SRE) to join our Forward Engineering team. You will be the guardian of our production ecosystems, ensuring that our complex, data-driven AI platforms remain resilient, scalable, and highly performant. This role is a hybrid of software engineering and systems architecture, with a specialized focus on MLOps—bridging the gap between model development and production-grade reliability.
Key Responsibilities
1. Reliability & Performance Engineering
•
SLA/SLO Management: Define, monitor, and maintain Service Level Objectives (SLOs) and Service Level Indicators (SLIs) for critical AI/ML services.
•
Error Budgeting: Manage error budgets to balance the velocity of feature releases from the ML team with the stability of the production environment.
•
Scalability: Architect and manage auto-scaling strategies for Kubernetes (GKE) to handle fluctuating workloads during model training and high-volume inference.
2. MLOps & AI Infrastructure
•
Model Serving Reliability: Ensure the high availability of Vertex AI endpoints and custom inference services.
•
GPU/TPU Optimization: Monitor and optimize compute resource utilization (accelerators) to ensure cost-efficient performance for Large Language Models (LLMs).
•
Pipeline Resilience: Support and stabilize ML pipelines (Vertex AI Pipelines/Kubeflow) to ensure seamless data flow from ingestion to model retraining.
3. Automation & Orchestration (Eliminating “Toil”)
•
Infrastructure as Code (IaC): Use Terraform or Pulumi to provision and manage consistent, version-controlled cloud environments.
•
CI/CD & GitOps: Design and optimize robust deployment pipelines for both application code and ML models using GitHub Actions, Cloud Build, or ArgoCD.
•
Task Automation: Develop custom Python or Go scripts to automate repetitive operational tasks, self-healing mechanisms, and resource cleanup.
4. Monitoring, Alerting & Incident Response
•
Observability: Build and manage comprehensive dashboards using Prometheus, Grafana, or Google Cloud Operations Suite (Stackdriver).
•
Incident Management: Act as a primary responder in on-call rotations, leading the technical resolution of production outages.
•
Blameless Post-Mortems: Conduct deep-dive root cause analysis (RCA) to ensure systemic issues are identified and permanently remediated through code.
Requirements
Orchestration: Expert-level knowledge of Kubernetes (K8s) and Docker.
MLOps Stack: Familiarity with tools such as Kubeflow, Vertex AI, MLflow, or DVC.
Scripting: Strong proficiency in Python (for automation) and Bash; knowledge of Go is a plus.
Data Systems: Experience managing the reliability of data-heavy services (BigQuery, Pub/Sub, or Vector Databases like Pinecone/Milvus).
Networking: Solid understanding of VPCs, Load Balancers, DNS, and secure service mesh (Istio/Anthos).
Benefits
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
More roles at Tiger Analytics Inc.
Sr. Analytics ConsultantSr. Analytics ConsultantBusiness Analyst (Financial Crime Compliance)UI Path + Azure AI EngineersSr. Manager/ Associate Director - Engagement Lead (CPG/Retail)
Seekless
Seek less: one search across companies' own career pages, instead of a dozen job boards.
Product
Find jobsCompaniesPricingFree Resume CheckerBlog
Legal
AboutPrivacyTermsCookies
© 2026 SEEKLESS. ALL RIGHTS RESERVED.BUILT WITH CARE