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# AI/ML Platform Engineer

- **Company:** Toyota Financial Services
- **Location:** United States
- **Experience:** Starter
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software as a Service, Cloud Foundry, Software Quality, Encodings, Computer Programming, Computer Engineering, Data Stores, DevOps, Python (Programming Language), Azure Machine Learning, Software Deployment, Software Engineering, TypeScript, Retrieval-Augmented Generation, Delivery Pipeline, Large Language Models, Cloudformation, Infrastructure Automation Frameworks, Information Technology, Amazon Bedrock, Deployment Automation, Machine Learning Operations, Terraform, Prompt Orchestration, Software Version Control, Docker
- **Published:** October 11, 2026
- **Apply:** https://www.dice.com/job-detail/1826ffe3-6f6c-4ec7-8bce-91748d1bda03

## About the Role

Toyota Financial Services Enterprise Platforms team is looking for a passionate and highly motivated AI/ML Platform Engineer. This role helps build and operate cloud-native platform capabilities that enable enterprise MLOps and LLMOps and support AI/ML and GenAI application delivery. You will contribute hands-on engineering across APIs, services, deployment pipelines, and platform automation, working closely with senior engineers, architecture, platform, data, and product teams.

This is an early-career software engineering role for candidates with 1-3 years of professional experience who are eager to grow their skills and take ownership of features and services in production under the guidance of senior team members., * 2 or more years of professional software engineering experience.

 * Bachelor's degree or higher in Computer Science, Computer Engineering, or a related technical field.
 * Strong programming skills in one or more of the following: Python, or JavaScript/TypeScript.
 * Experience building and operating cloud-based applications and services on AWS or similar cloud providers.
 * Exposure to DevOps practices such as CI/CD pipelines, version control (Git/GitHub), containers (Docker), and automated deployments.
 * Strong analytical, problem-solving, communication, and cross-team collaboration skills.
 * Eagerness to learn AI/ML platform engineering and grow under mentorship.

Added bonus if you have

 * Hands-on exposure to AI/ML platform tools and patterns (MLOps/LLMOps fundamentals).
 * Exposure to GenAI workloads such as RAG pipelines, embedding workflows, prompt orchestration, or model inference services.
 * Familiarity with infrastructure-as-code (Terraform, CDK, or CloudFormation).
 * Familiarity with AWS AI/ML services (SageMaker, Bedrock).

## Description

* Design, build, test, and maintain cloud-native platform components and services that support AI/ML and LLM workloads.
 * Help implement and operate MLOps and LLMOps capabilities such as model deployment pipelines, monitoring, and operational reliability.
 * Build integrations with AWS AI/ML services such as Amazon SageMaker and Amazon Bedrock, along with model registries, vector data stores, model endpoints, and orchestration tooling.
 * Help build and maintain CI/CD pipelines, infrastructure-as-code, and deployment automation in collaboration with platform and DevOps engineering teams.
 * Troubleshoot production issues, analyze system metrics, and support improvements for reliability, latency, and cost.
 * Follow engineering standards for code quality, testing, documentation, and Agile delivery.
 * Continuously learn evolving AI/ML platform technologies and engineering best practices.