Toyota North America · 11 hours ago
AWS DevOps Engineer (With deep expertise in MLOps)
Plano, TX
Full-time
Onsite
Senior Level
5+ years expToyota North America is a leading automotive company that is committed to innovation and enhancing lives through high-quality solutions. They are seeking a seasoned AWS DevOps Engineer with deep expertise in MLOps to design and support a scalable SageMaker platform, thereby empowering data scientists in the machine learning lifecycle.
Manufacturing
No H1B
Responsibilities
Design, deploy, and maintain a robust AWS SageMaker platform to support the full ML lifecycle: data preparation, model training, tuning, deployment, monitoring, and retraining
Collaborate closely with data scientists to productionize machine learning models, ensuring scalability, reliability, and performance
Implement model versioning, lineage tracking, and governance to support reproducibility and auditability
Build and maintain MLOps pipelines that automate continuous integration, continuous delivery (CI/CD), and continuous training (CT) of ML models
Manage AWS infrastructure including EC2, ECS Fargate, ALB, S3, DynamoDB, OpenSearch, and AWS Bedrock to support AI/ML workloads
Enforce enterprise security best practices using IAM, Guardrails, and AWS security services
Configure and manage Single Sign-On (SSO) integration with Okta and Mulesoft proxy for secure platform access
Automate infrastructure provisioning and management using Infrastructure as Code (IaC) tools such as Terraform and OpenTofu
Monitor deployed models and infrastructure for performance, drift, and anomalies; implement alerting and remediation workflows
Support containerized microservices architecture with Python-based services, establishing CI/CD pipelines for rapid deployment
Stay current with AWS services, MLOps frameworks, AI ecosystem trends, and DevOps best practices
Qualification
Required
5+ years of hands-on experience in AWS cloud infrastructure and DevOps engineering with a strong focus on MLOps
Expertise in AWS services: SageMaker (including SageMaker Pipelines, Model Registry), ECS Fargate, EC2, ALB, S3, DynamoDB, OpenSearch, AWS Bedrock
Proven experience in productionizing ML models, managing model versioning, lineage, and lifecycle
Strong skills in Infrastructure as Code using Terraform and OpenTofu
Experience designing and implementing CI/CD pipelines for ML workflows and Python microservices
Deep understanding of AWS security best practices, IAM policies, Guardrails, and enterprise security frameworks
Experience integrating Single Sign-On (SSO) solutions using Okta and Mulesoft proxy
Familiarity with ML lifecycle management tools and frameworks
Strong scripting and automation skills
Excellent problem-solving, collaboration, and communication skills
Preferred
AWS certifications (e.g., AWS Certified DevOps Engineer, AWS Certified Machine Learning Specialty)
Experience with container orchestration, microservices, and serverless architectures
Knowledge of monitoring, logging, and alerting tools for ML models and cloud infrastructure
Familiarity with open-source MLOps tools (e.g., MLflow, Kubeflow)
Benefits
A work environment built on teamwork, flexibility, and respect
Professional growth and development programs to help advance your career, as well as tuition reimbursement
Team Member Vehicle Purchase Discount.
Toyota Team Member Lease Vehicle Program (if applicable).
Comprehensive health care and wellness plans for your entire family
Toyota 401(k) Savings Plan featuring a company match, as well as an annual retirement contribution from Toyota regardless of whether you contribute
Paid holidays and paid time off
Company
Toyota North America
At Toyota, we’re known for making some of the highest quality vehicles on the road. But there is more to our story.
10001+ employees
Funding
Current Stage
Late StageTotal Funding
$4.5MKey Investors
ARPA-E
2024-12-18Grant· $4.5M
Leadership Team
Tetsuo Ogawa
CEO
Brian Kursar
Group Vice President - Head of Enterprise AI
Recent News
Morningstar.com
2026-01-05
2026-01-05
Company data provided by crunchbase