Senior ML/AI Engineer — End-to-End Production ML

Toyota; Plano (AL); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Healthcare plans

Tuition reimbursement

Vehicle Purchase Discount

Relocation assistance

Job summary

Toyota is seeking a Lead Engineer in ML/AI to design, deploy, and monitor production-grade ML systems on AWS. You will own end-to-end ML features, lead LLM integration, and guide model choice and deployment strategies.

The role emphasizes collaboration with product, data science, and engineering teams to deliver AI-powered capabilities. Ideal candidates have strong ML fundamentals, experience with PyTorch/TensorFlow, and hands-on work with Bedrock/SageMaker in production environments.

Qualifications

• 5+ years of software engineering, with 2–4 years focused on ML/AI in production.
• Strong ML fundamentals including transformers, CNNs, RNNs and evaluation methods.
• Hands-on with large language models: prompt engineering, RAG, embeddings and vector stores.

Responsibilities

• Design, build, and maintain end-to-end ML pipelines from data ingestion to deployment and monitoring.
• Lead integration of large language models into product features using prompt engineering and RAG.
• Choose appropriate approaches: Bedrock, SageMaker, or classical ML for different problems.
• Own ML features from design through post-launch monitoring and observability.
• Contribute to technical design discussions across ML architecture and tooling.

Skills

Python

ML fundamentals

Large language models

AWS ML services

PyTorch

TensorFlow

JAX

LangChain

MLOps

Education

Bachelor's degree in Computer Science, Machine Learning, Statistics, or related field

Master's degree in Machine Learning, AI, CS, or related field

Tools

Amazon Bedrock

SageMaker

Lambda

Step Functions

S3

EventBridge

SQS

SNS

OpenSearch

Hugging Face Transformers

scikit-learn

Job description

Toyota is seeking a Lead Engineer in ML/AI to design, deploy, and monitor production-grade ML systems on AWS. You will own end-to-end ML features, lead LLM integration, and guide model choice and deployment strategies.

The role emphasizes collaboration with product, data science, and engineering teams to deliver AI-powered capabilities. Ideal candidates have strong ML fundamentals, experience with PyTorch/TensorFlow, and hands-on work with Bedrock/SageMaker in production environments.