Security AI / ML Engineer, Lead
Toyota North America7 days ago
Plano, TX, USAStaff+
Responsibilities
- Design and implement prompt engineering patterns for managed AI service integration.
- Build, curate, label, and version training datasets from enterprise security telemetry.
- Fine-tune models for alert triage, risk scoring, and finding classification using organization-specific security data.
- Create analyst feedback loops that capture approval and rejection signals for continuous model improvement and retraining.
- Build model evaluation frameworks using automated metrics and human agreement benchmarks.
- Design and implement model routing based on task complexity, latency requirements, and cost.
- Monitor production models for drift, accuracy degradation, and emerging failure modes.
- Implement centralized token usage monitoring for AI consumption visibility and cost control.
- Collaborate on multi-agent architectures, tool use, and autonomous triage workflows.
- Deploy and manage model inference endpoints across cloud ML services and container-based serving.
Requirements
- At least 3 years of applied ML/AI engineering experience with production deployment, rather than research-only experience.
- Hands-on experience fine-tuning LLMs with LoRA, QLoRA, or full fine-tuning on domain-specific data.
- Experience with cloud ML platforms such as AWS SageMaker, including training jobs, hyperparameter tuning, model registries, and endpoint deployment.
- Proficiency in PyTorch for model training and custom architectures.
- Experience building evaluation pipelines with automated metrics, human evaluation protocols, and A/B testing.
- Understanding of transformer architectures and attention mechanisms beyond API usage.
- Fluency in Python and production engineering practices.
- Strong communication skills for explaining model behavior and limitations to non-ML stakeholders.
- Preferred experience with cybersecurity data, alert classification, threat detection, or anomaly detection.
- Preferred familiarity with vLLM, Triton Inference Server, Tensor RT optimization, and the Hugging Face ecosystem, including Model Hub, tokenizers, datasets, and PEFT.
- Preferred experience with RAG architectures, vector databases, multi-model routing, mixture-of-experts approaches, agentic AI patterns, and model cost optimization.
Benefits
- Teamwork-focused, flexible, and respectful work environment.
- Professional growth and development programs with tuition reimbursement.
- Team Member Vehicle Purchase Discount and Toyota Team Member Lease Vehicle Program where applicable.
- Comprehensive health care and wellness plans for the employee’s family.
- Toyota 401(k) Savings Plan with company match and an annual retirement contribution where applicable.
- Paid holidays and paid time off.
- Referral services for prenatal services, adoption, childcare, schools, and more.
- Tax-advantaged Health Savings Account, Health Care FSA, and Dependent Care FSA.
- Relocation assistance where applicable.
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?