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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI/ML Platform Engineer - **Company:** Toyota Motor Sales, U.S.A., Inc. - **Location:** Plano, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Audit Trail, Data Stores, Github, Identity and Access Management, Machine Learning, Performance Tuning, Prometheus, Azure Machine Learning, Software Engineering, Software Technical Review, Datadog, Data Logging, System Availability, Delivery Pipeline, Large Language Models, Grafana, Cloudformation, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Machine Learning Operations, Cloudwatch, Terraform, Jenkins, Microservices - **Published:** July 16, 2026 - **Apply:** https://www.juju.com/job/00000000ggze2c ## About the Role Toyota Financial Services Enterprise Platforms team is seeking a highly skilled **Senior AI/ML Platform Engineer** to help our growing ML, AI and GenAI platform infrastructure needs. As a Senior AI/ML Platform Engineer, you will design, build, and support scalable platform capabilities that enable enterprise MLOps and LLMOps. You will work independently on features and services, while partnering with product owners to understand business requirements, aligning with architecture direction, and collaborating with platform engineering, data, and cybersecurity teams to deliver secure, reliable, and performant environments for model training, inference, orchestration, and retrieval-augmented generation (RAG) use cases. The ideal candidate will have demonstrated hands-on experience in cloud and platform engineering and ability to execute independently while collaborating effectively across technical and business teams., + Bachelor's degree that provides a strong foundation in software engineering or related fields. + 6+ years of software engineering experience with solid expertise in cloud platforms or infrastructure engineering. + 2+ years of hands-on experience building or supporting infrastructure for AI/ML workloads (training and/or inference). + Proficiency with AWS services and infrastructure-as-code tools such as Terraform, CDK, or CloudFormation. + Hands-on experience with Kubernetes (EKS or equivalent), containers, and CI/CD pipelines. + Working knowledge of scalable microservice patterns and platform reliability practices. + Familiarity with observability tools like Datadog, CloudWatch, or Prometheus. + Strong skills in Git/GitHub and CI/CD tools such as GitHub Actions or Jenkins. + Added bonus if you have: + Familiarity with AWS AI/ML services like SageMaker or Bedrock. + Experience with LLMOps and GenAI platform patterns such as LangChain, RAG pipelines, or embedding workflows. + Exposure to vector databases and model registries. + AWS Solutions Architect Associate or Machine Learning certifications. ## Description + Design, build, and enhance cloud-native platform components for AI/ML and LLM workloads in production environments. + Implement and operate MLOps and LLMOps capabilities including model training workflows, deployment pipelines, monitoring, and rollback support. + Build and optimize containerized and GPU-enabled runtime environments for efficient model serving and inference. + Integrate platform services such as model registries, vector data stores, and orchestration tooling to streamline workflows. + Develop reusable patterns for inference services, prompt flow integration, and performance tuning to maximize platform efficiency. + Implement secure-by-default controls including access management, logging, and auditability for AI platform services. + Partner with engineering, data, and cybersecurity teams to enhance observability, resiliency, and operational readiness. + Contribute to technical design reviews and establish engineering standards for AI/ML platform services. + Troubleshoot production issues, perform root cause analysis, and drive continuous improvements to the platform. + Stay current with evolving AI/ML platform technologies and best practices to keep Toyota at the forefront of innovation. ## Related Videos - [Inside Mercedes-Benz: 140 Years of Heritage meet AI](https://www.wearedevelopers.com/videos/100054-inside-mercedes-benz-140-years-of-heritage-meet-ai) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [All your telemetry data from any source in one place](https://www.wearedevelopers.com/videos/57-all-your-telemetry-data-from-any-source-in-one-place) - [Our GitOps approach for deploying an Identity Provider and an API Gateway in a SaaS company](https://www.wearedevelopers.com/videos/776-our-gitops-approach-for-deploying-an-identity-provider-and-an-api-gateway-in-a-saas-company) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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