Sr. Site Reliability Engineer, MLOps, Infrastructure Engineering

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.

Responsibilities:
Mature our Machine Learning Operations Platform and advocate best practices to MLops engineers
Design and implement scalable, automated workflows for the complete ML lifecycle
Maintain Kubernetes-based infrastructure for model training, deployment, and monitoring
Develop solutions for workload orchestration and time-slicing using tools like Flyte and Ray
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 using React to 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

Requirements:
Strong hands-on experience with tools and frameworks like Kubernetes, Kubeflow, MLflow, Flyte / Ray
Proven experience with React for building interactive web applications, especially self-service portals that enhance the user experience for managing ML pipelines and workflows
Expertise in MIG, time-slicing, and scaling AI workloads efficiently
Proficiency in Python, Golang and bash for pipeline development, 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 in Kubernetes workloads, networking, and CI/CD pipelines are required

Compensation & Benefits:
Benefits

Along with competitive pay, as a full-time Tesla employee, you are eligible for the following benefits at day 1 of hire:
Medical plans > plan options with $0 payroll deduction
Family-building, fertility, adoption and surrogacy benefits
Dental (including orthodontic coverage) and vision plans, both have options with a $0 paycheck contribution
Company Paid (Health Savings Accounts) HSA Contribution when enrolled in the High-Deductible medical plan with HSA
Healthcare and Dependent Care Flexible Spending Accounts (FSA)
401(k) with employer match, Employee Stock Purchase Plans, and other financial benefits
Company paid Basic Life, AD&D
Short-term and long-term disability insurance (90 day waiting period)
Employee Assistance Program
Sick and Vacation time (Flex time for salary positions, Accrued hours for Hourly positions), and Paid Holidays
Back-up childcare and parenting support resources
Voluntary benefits to include: critical illness, hospital indemnity, accident insurance, theft & legal services, and pet insurance
Weight Loss and Tobacco Cessation Programs
Tesla Babies program
Commuter benefits
Employee discounts and perks program

Expected Compensation
$140,000 - $300,000/annual salary + cash and stock awards + benefitsPay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.