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# Sr. Site Reliability Engineer, MLOps, Infrastructure Engineering

- **Company:** Tesla Motors
- **Location:** Fremont, CA, United States
- **Experience:** Expert
- **Salary:** $140,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Bash Shell, Cloud Computing, Configuration Management, Computer Engineering, Continuous Integration, Linux, DevOps, Monitoring of Systems, Python (Programming Language), Performance Tuning, Reliability Engineering, Ansible, Prometheus, Web Applications, Google Cloud, Grafana, Kubernetes Helm Charts, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Machine Learning Operations, Splunk, Golang
- **Published:** June 22, 2026
- **Apply:** https://diversityjobs.com/career/13949966/Sr-Site-Reliability-Engineer-Ai-Infrastructure-California-Fremont

## About the Role

* Strong hands-on experience with tools and frameworks likeKubernetes,Kubeflow,MLflow,Flyte /Ray
 * Proven experience withReactfor building interactive web applications, especially self-service portals that enhance the user experience for managing ML pipelines and workflows
 * Expertise inMIG,time-slicing, and scalingAI workloadsefficiently
 * Proficiency in Python, Golang and bash for pipelinedevelopment, and automation
 * Proficiency with Linux fundamentals and performance optimizations
 * Experience with configuration management software (Ansible, etc.), systems monitoring & alerting (Prometheus, Grafana, Telegraf, Splunk, etc.)
 * Strong analytical and problem-solving abilities to troubleshoot and optimize AI/ML systems
 * Ability to collaborate with cross-functional teams, including data scientists, data engineers, and DevOps engineers, to deliver high-quality solutions.Excellent troubleshooting skills in production
 * Degree in Computer Science, Computer Engineering, Electrical Engineering, Physics or proof of exceptional skills in related field or equivalent experience
 * Strong troubleshooting skills inKubernetes workloads, networking, and CI/CD pipelinesare required

## Description

Our team manages multiple functions across Tesla that includes Devops,MLOps, Cloud Infrastructure (AWS, Azure, GCP), Factory SRE as well. Continued development and automation of deployment, monitoring, self-healing and alerting processes is imperative to the success of our engineering groups. As a Site Reliability Engineer, you will be responsible for maintaining and improving our platform to ensure our cross functional teams have the necessary tools and resources to be productive.
What You'll Do

 * Mature our Machine Learning Operations Platform and advocate best practices toMLopsengineers
 * Design and implement scalable, automated workflows for the complete ML lifecycle
 * MaintainKubernetes-based infrastructure for model training, deployment, and monitoring
 * Develop solutions for workload orchestration and time-slicing using tools likeFlyteandRay
 * Collaborate with engineers to build and maintain robust, pipelines for training and inference workflows
 * Develop Infrastructure-as-Code (IaC) solutions for deploying and managing cloud/on-prem ML environments
 * Design and develop intuitive, user-friendly self-service portals usingReactto enable data scientists and engineers to manage ML pipelines, monitor models, and access resources seamlessly
 * Package & deploy applications using Helm charts / deploy via ArgoCD
 * Participate in 24x7 on-call rotation


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