Lead ML/AI Engineer
Toyota North America7 days ago
Plano, TX, USAStaff+
Responsibilities
- Design, build, and maintain end-to-end ML pipelines from data ingestion and feature engineering through model training, evaluation, deployment, and monitoring.
- Integrate large language models into product features using prompt engineering, retrieval-augmented generation, and agent-based patterns.
- Select and apply Amazon Bedrock, SageMaker, classical ML, or hybrid approaches for different use cases.
- Own ML features from design through deployment, including testing, observability, and post-launch monitoring.
- Contribute technical proposals, architecture decisions, and tradeoff analysis across ML tooling and systems.
- Debug training, data pipeline, inference latency, and model drift issues across ML systems.
- Write production-quality ML code, participate in code reviews, and address data quality and ML technical debt.
- Mentor junior and mid-level engineers through pairing, reviews, and knowledge sharing.
- Collaborate with Product, Data Science, Front-End, and Backend Engineering teams to deliver AI-powered features.
Requirements
- Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field, or equivalent practical experience.
- 5+ years of software engineering experience, including 2–4 years focused on production ML/AI.
- Knowledge of supervised and unsupervised learning, deep learning architectures, optimization, and model evaluation.
- Hands-on experience with LLMs, prompt engineering, RAG pipelines, embedding models, vector databases, and agent frameworks.
- Experience with AWS AI/ML services and related data, eventing, orchestration, search, and infrastructure tools.
- Strong Python proficiency and production-quality software development experience.
- Experience with PyTorch, TensorFlow, or JAX, and libraries including Hugging Face Transformers, scikit-learn, and XGBoost.
- Familiarity with MLOps practices, experiment tracking, model registries, and CI/CD for ML workflows.
- Experience with ETL pipelines, feature stores, data validation, and structured and unstructured data.
- Understanding of infrastructure as code using AWS CDK, CloudFormation, or Terraform.
- Experience monitoring ML systems, including model performance, data drift, and alerting.
- Preferred qualifications include a master's degree, financial services experience, responsible AI expertise, NLP, inference optimization, containerized ML workloads, computer vision or multimodal systems, GraphQL or API gateway experience, AWS certifications, and open-source ML contributions.
Benefits
- Team-oriented and flexible work environment with professional growth and development programs.
- Tuition reimbursement and Toyota team member vehicle purchase and lease programs where applicable.
- Comprehensive health care and wellness plans for the employee's family.
- Toyota 401(k) plan with company matching and an annual retirement contribution where applicable.
- Paid holidays and paid time off.
- Referral services for prenatal services, adoption, childcare, schools, and related needs.
- Health Savings Account, Health Care FSA, and Dependent Care FSA options.
- Relocation assistance where 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?