Senior Engineering Lead - ML/AI Engineering
Required Skills
Job Description
**Overview**
**Who we are**
Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As one of the world’s most admired brands, Toyota is growing and leading the future of mobility through innovative, high\-quality solutions designed to enhance lives and delight those we serve. We’re looking for talented team members who want to Dream. Do. Grow. with us.
An important part of the Toyota family is Toyota Financial Services (TFS), the finance and insurance brand for Toyota and Lexus in North America. While TFS is a separate business entity, it is an essential part of this world\-changing company\- delivering on Toyota's vision to move people beyond what's possible. At TFS, you will help create best\-in\-class customer experience in an innovative, collaborative environment.
***To save time applying, Toyota does not offer sponsorship of job applicants for employment\-based visas or any other work authorization for this position at this time.***
**Who we're looking for**
At TFS, we're building next\-generation products that redefine mobility for millions of customers worldwide. We're looking for a **Sr Lead Engineer** — an individual contributor at the principal level — who brings deep expertise in machine learning, AI systems, and large language models, combined with the engineering rigor to ship production\-grade intelligent systems on AWS.
This isn't a management role. It's for the engineer who sees the signal in the noise: the one who can take a business problem, frame it as an ML challenge, build the model, deploy the pipeline, and make it reliable at scale. You'll shape our AI strategy from the ground up, work across teams to embed intelligence into our products, and mentor engineers who want to grow in this space. If you want to do meaningful applied AI work — not just research, not just wrappers around APIs — this is the role.
**This position is based in Plano, TX. The selected candidate will be expected to reside within a commutable distance of this location.**
**Key Responsibilities**
* Serve as the technical authority for ML/AI architecture across one or more product domains, making high\-impact decisions on model selection, training strategies, inference patterns, and tooling
* Design, build, and maintain end\-to\-end ML pipelines — from data ingestion and feature engineering to model training, evaluation, deployment, and monitoring
* Lead the integration of large language models into production systems, including prompt engineering, fine\-tuning, retrieval\-augmented generation (RAG), and agent\-based architectures
* Evaluate and select the right approach for each problem: foundation models via **Amazon Bedrock**, custom training on **SageMaker**, classical ML, or hybrid approaches
* Lead technical design reviews, architecture discussions, and RFC processes for AI/ML initiatives — driving alignment across engineering teams
* Identify and resolve systemic issues: model drift, data quality gaps, latency bottlenecks, cost inefficiencies, and scaling constraints in ML systems
* Define and champion engineering best practices for ML: experiment tracking, model versioning, reproducibility, testing strategies, and responsible AI principles
* Collaborate closely with Engineering Managers, Product, Data Science, and Front\-End/Backend Engineering to shape roadmaps and ensure technical feasibility of AI\-powered features
* Mentor and grow engineers at all levels through code reviews, pairing, design feedback, and technical guidance on ML/AI topics
* Contribute to hiring by conducting technical interviews and helping define what great looks like for ML/AI engineering at TFS
* Proactively communicate technical risks, tradeoffs, and recommendations to both engineering and non\-technical stakeholders
**What you bring**
* Bachelor's degree in Computer Science, Machine Learning, Statistics, or related field, or equivalent practical experience
* 7\+ years of software engineering experience, including 3–5 years focused specifically on ML/AI in production, with a track record of operating at a principal or staff engineer level
* Deep understanding of **machine learning fundamentals**: supervised and unsupervised learning, deep learning architectures (transformers, CNNs, RNNs), optimization techniques, and evaluation methodologies
* Hands\-on experience with **large language models**: prompt engineering, fine\-tuning (LoRA, QLoRA), RAG pipelines, embedding models, vector databases, and agent frameworks (LangChain, LlamaIndex, or similar)
* Production experience with **AWS AI/ML services**, including:
+ **Amazon Bedrock** for foundation model access, fine\-tuning, and knowledge bases or
+ **Amazon SageMaker** for custom model training, hosting, and MLOps pipelines
+ **Lambda** and **Step Functions** for orchestrating inference workflows
+ **S3** for data lakes and model artifact storage
+ **EventBridge**, **SQS**, or **SNS** for event\-d
**Who we are**
Collaborative. Respectful. A place to dream and do. These are just a few words that describe what life is like at Toyota. As one of the world’s most admired brands, Toyota is growing and leading the future of mobility through innovative, high\-quality solutions designed to enhance lives and delight those we serve. We’re looking for talented team members who want to Dream. Do. Grow. with us.
An important part of the Toyota family is Toyota Financial Services (TFS), the finance and insurance brand for Toyota and Lexus in North America. While TFS is a separate business entity, it is an essential part of this world\-changing company\- delivering on Toyota's vision to move people beyond what's possible. At TFS, you will help create best\-in\-class customer experience in an innovative, collaborative environment.
***To save time applying, Toyota does not offer sponsorship of job applicants for employment\-based visas or any other work authorization for this position at this time.***
**Who we're looking for**
At TFS, we're building next\-generation products that redefine mobility for millions of customers worldwide. We're looking for a **Sr Lead Engineer** — an individual contributor at the principal level — who brings deep expertise in machine learning, AI systems, and large language models, combined with the engineering rigor to ship production\-grade intelligent systems on AWS.
This isn't a management role. It's for the engineer who sees the signal in the noise: the one who can take a business problem, frame it as an ML challenge, build the model, deploy the pipeline, and make it reliable at scale. You'll shape our AI strategy from the ground up, work across teams to embed intelligence into our products, and mentor engineers who want to grow in this space. If you want to do meaningful applied AI work — not just research, not just wrappers around APIs — this is the role.
**This position is based in Plano, TX. The selected candidate will be expected to reside within a commutable distance of this location.**
**Key Responsibilities**
* Serve as the technical authority for ML/AI architecture across one or more product domains, making high\-impact decisions on model selection, training strategies, inference patterns, and tooling
* Design, build, and maintain end\-to\-end ML pipelines — from data ingestion and feature engineering to model training, evaluation, deployment, and monitoring
* Lead the integration of large language models into production systems, including prompt engineering, fine\-tuning, retrieval\-augmented generation (RAG), and agent\-based architectures
* Evaluate and select the right approach for each problem: foundation models via **Amazon Bedrock**, custom training on **SageMaker**, classical ML, or hybrid approaches
* Lead technical design reviews, architecture discussions, and RFC processes for AI/ML initiatives — driving alignment across engineering teams
* Identify and resolve systemic issues: model drift, data quality gaps, latency bottlenecks, cost inefficiencies, and scaling constraints in ML systems
* Define and champion engineering best practices for ML: experiment tracking, model versioning, reproducibility, testing strategies, and responsible AI principles
* Collaborate closely with Engineering Managers, Product, Data Science, and Front\-End/Backend Engineering to shape roadmaps and ensure technical feasibility of AI\-powered features
* Mentor and grow engineers at all levels through code reviews, pairing, design feedback, and technical guidance on ML/AI topics
* Contribute to hiring by conducting technical interviews and helping define what great looks like for ML/AI engineering at TFS
* Proactively communicate technical risks, tradeoffs, and recommendations to both engineering and non\-technical stakeholders
**What you bring**
* Bachelor's degree in Computer Science, Machine Learning, Statistics, or related field, or equivalent practical experience
* 7\+ years of software engineering experience, including 3–5 years focused specifically on ML/AI in production, with a track record of operating at a principal or staff engineer level
* Deep understanding of **machine learning fundamentals**: supervised and unsupervised learning, deep learning architectures (transformers, CNNs, RNNs), optimization techniques, and evaluation methodologies
* Hands\-on experience with **large language models**: prompt engineering, fine\-tuning (LoRA, QLoRA), RAG pipelines, embedding models, vector databases, and agent frameworks (LangChain, LlamaIndex, or similar)
* Production experience with **AWS AI/ML services**, including:
+ **Amazon Bedrock** for foundation model access, fine\-tuning, and knowledge bases or
+ **Amazon SageMaker** for custom model training, hosting, and MLOps pipelines
+ **Lambda** and **Step Functions** for orchestrating inference workflows
+ **S3** for data lakes and model artifact storage
+ **EventBridge**, **SQS**, or **SNS** for event\-d
Posted: 2026-03-19