Lead AI/ML Platform Engineer
Toyota North America10 days ago
Plano, TX, USAStaff+
Responsibilities
- Design and implement cloud-native infrastructure for enterprise AI/ML and GenAI workloads in production.
- Build and evolve MLOps and LLMOps capabilities for model training, versioning, deployment, monitoring, and rollback.
- Create GPU-accelerated compute environments and develop model-serving, inference-scaling, prompt-management, and latency-optimization solutions.
- Standardize infrastructure patterns for vector databases, model registries, and orchestration frameworks.
- Design secure, multi-tenant AI environments with access controls, auditability, and usage governance.
- Partner with engineering, platform, data, architecture, and cybersecurity teams to improve data flow, observability, and operational resiliency.
- Own technical direction for AI infrastructure services and integrations, lead design reviews, establish engineering standards, and guide technical decisions.
- Mentor engineers and support their growth through coaching, feedback, and development planning.
Requirements
- 10+ years of software engineering experience focused on cloud infrastructure or cloud platform engineering.
- 3+ years of experience building cloud infrastructure supporting AI/ML training, tuning, or inference workloads.
- Hands-on experience with AWS and infrastructure-as-code tools such as Terraform, CDK, or CloudFormation.
- Production experience with Kubernetes, containerization, and CI/CD pipelines.
- Strong understanding of GPU infrastructure, serverless compute, and scalable microservice patterns.
- Familiarity with model hosting, inference scaling, and observability tools such as Datadog, CloudWatch, or Prometheus.
- Practical experience with Git, GitHub, and CI/CD tools such as GitHub Actions or Jenkins.
- Preferred experience with AWS AI/ML services such as SageMaker or Bedrock; LLMOps and GenAI infrastructure such as LangChain or RAG pipelines; and vector databases, model registries, or orchestration tools such as MLflow, Airflow, or Ray.
- Preferred knowledge of prompt management, token usage optimization, and model performance tuning.
- AWS Solutions Architect Professional or machine learning certification is a bonus.
Benefits
- Team-oriented, flexible, and respectful work environment.
- Professional growth and development programs with tuition reimbursement.
- Team Member Vehicle Purchase Discount and Toyota Team Member Lease Vehicle Program, if applicable.
- Comprehensive health care and wellness plans for the employee's family.
- Toyota 401(k) Savings Plan with company match and an annual retirement contribution, if applicable.
- Paid holidays and paid time off.
- Referral services for prenatal services, adoption, childcare, schools, and related needs.
- Tax-advantaged Health Savings Account, Health Care FSA, and Dependent Care FSA.
- Relocation assistance, if applicable.
Tech Stack
Categories
About 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. We believe in putting people first and creating opportunities for our team members to build careers as unique as they are. As one of the world’s most admired brands, we are leading the way to the future of mobility, so everyone can move freely, happily and comfortably. We have big dreams and believe that nothing is impossible. Ready to Dream, Do and Grow with us?