Machine Learning Engineer

Yum! Brands’ is hiring Machine Learning Engineers to support the development and optimization of real-time AI systems that power the Taco Bell Voice AI experience. This role will focus on speech, natural language, and infrastructure-oriented ML tasks that help ensure performance, reliability, and adaptability of deployed voice agents.

You’ll collaborate closely with MLEs, AI Engineers, and QA to fine-tune and evaluate models, improve latency, and deliver on voice AI performance standards at drive-thru scale.

Responsibilities :

Model Development & Optimization

Train, fine-tune, and evaluate speech recognition (ASR), LLM, and NLU models

Contribute to model monitoring, evaluation pipelines, and test harnesses

Optimize for speed, robustness, and market variability

Deployment & Integration Support

Collaborate with MLEs and DevOps to validate models in staging and production

Participate in benchmarking across markets and environments (hardware, accents, menu dynamics)

Help investigate production issues and assist in triage / debugging

Collaboration & Experimentation

Work with AI Engineers to deploy prompt-based systems enhanced with learned representations

Pair with QA to improve model accuracy and regressions

Contribute to experiment design, data selection, and annotation loops.

Mandatory Skills

4-8 years of experience in applied machine learning or MLE roles.

Proficiency in Python and ML libraries such as PyTorch, TensorFlow, HuggingFace.

Experience in fine-tuning speech, ASR, or embedding models.

Deep experience with ML pipelines and model lifecycle management.

Hands-on with NLP / LLM modeling,Fine-tuning (LoRA / QLoRA), Embeddings & Prompt optimization.

Exposure on building evaluation frameworks for models.

Experience with ML ops elements : Model tracking (MLflow or similar),Experimentation workflows, Versioning + testing,AWS experience for model training + hosting.

Ability to work on : Model optimization,Latency / throughput tuning,Scalable inference architecture.

Preferred / good to have

Exposure on ASR / TTS models

Experience with : Conversation classification, Intent detection, Sentiment models.

Prior experience with deep learning frameworks (PyTorch, TensorFlow).

Knowledge of real-time inference systems.

Some understanding of Voice AI orchestration.