Senior ML Platform Engineer

Toyota North America•Plano, TX

About The Position

Toyota Financial Services Enterprise Platforms team is looking for a passionate and highly motivated Senior ML Platform Engineer. The primary responsibility of this role is to design, build, and operationalize an enterprise-grade ML platform on AWS SageMaker Unified Studio. You will lead the organization’s migration from a fragmented ML toolchain to a unified, governed environment, directly impacting how we handle the full ML lifecycle—from initial data discovery to production deployment and monitoring. Reporting to the Enterprise Platforms leadership, the person in this role will support the team’s objective to scale our ML infrastructure and empower data teams to deliver high-impact AI solutions with speed and reliability.

Requirements

A bachelor’s degree in a relevant field that provides a strong foundation in software engineering, cloud platforms, or machine learning
7+ years of software engineering experience in cloud infrastructure or ML platform operations, with experience navigating complex production environments
4+ years of hands-on AWS experience, including Amazon SageMaker Studio, Pipelines, Model Registry, Endpoints, and Feature Store
3+ years of experience building and operating production MLOps pipelines, including training, versioning, deployment, and rollback strategies
Proficiency with infrastructure-as-code tools such as Terraform, CDK, or CloudFormation to build repeatable, scalable environments
Deep understanding of IAM design for ML, including execution roles, service roles, and cross-account access management
Strong collaboration and communication skills, with the ability to work independently while partnering effectively across teams

Nice To Haves

Advanced knowledge of SageMaker Unified Studio, including domain provisioning, custom blueprints, and project standardization
Hands-on experience with SageMaker Feature Store for online and offline feature management
Experience using SageMaker Model Monitor for data quality checks, bias detection, and drift detection
An AWS Machine Learning Specialty certification that demonstrates deeper technical expertise

Responsibilities

Architect cloud-native platform capabilities that power production ML workloads and support enterprise-scale adoption
Drive platform standardization by standing up SageMaker Unified Studio, including domain configuration, project provisioning, and persona-based access
Build and maintain automated MLOps pipelines that streamline data extraction, training, model registration, and deployment
Govern the ML lifecycle through model versioning, lineage tracking, and cross-account promotion using SageMaker Model Registry
Enable reproducible experimentation by configuring MLflow for robust tracking of parameters, metrics, and artifacts
Strengthen platform security by implementing identity and access controls with Okta SSO and SailPoint
Deliver reliable real-time and batch prediction workflows while proactively monitoring model performance, drift, and data quality
Own platform observability and operational excellence through CloudWatch, Datadog, and root cause analysis
Collaborate across technical and business teams to improve workflows, remove friction, and accelerate delivery of AI solutions

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
Referral services related to prenatal services, adoption, childcare, schools, and more
Tax Advantage Accounts (Health Savings Account, Health Care FSA, Dependent Care FSA
Relocation assistance (if applicable)