Machine Learning - Machine Learning

Title: Manager, Machine Learning Location: Irvine, CA Duration: 6 Months Job Description: We are hiring a Manager, Machine Learning (MLE) to lead the development and operationalization of machine learning systems powering the Voice AI experience. This role is central to ensuring performance, scalability, and reliability across real-time models that support speech, natural language understanding, and agent behavior. You will manage a team of MLEs and partner with AI Engineers, QA, and DevOps to deliver high-quality agent performance with a strong focus on latency, integration with restaurant systems (e.g., HME, POS), and production excellence. Key Responsibilities ML System Design & Architecture • Lead the design of end-to-end ML pipelines for speech, ASR, and NLU modules • Optimize model performance for real-time interaction, including latency, uptime, and inference cost • Implement and evolve model evaluation, testing, and monitoring frameworks Infrastructure & Integration • Collaborate with engineering to integrate ML components with external systems (HME, menu boards, POS) • Support scalable deployment strategies across markets and environments • Drive MLOps best practices in CI/CD, rollback, logging, and observability Leadership & Collaboration • Mentor and guide a team of MLEs and junior ML engineers • Partner with product, AI engineering, and QA to define technical scope, delivery targets, and quality standards • Support internal upskilling and technical review of AI-driven components Required Qualifications • 6+ years of experience in machine learning, including at least 2 years in technical leadership roles • Proven expertise in deploying NLP, ASR, or LLM-based systems in real-time applications • Strong programming skills in Python and ML tooling (e.g., PyTorch, HuggingFace, ONNX, MLflow) • Experience optimizing model latency and integrating ML with backend infrastructure Preferred Qualifications • Experience in QSR, retail, or voice-driven customer service environments • Background in integrating AI with physical systems (HME, POS, IoT) • Familiarity with LoRA, quantization, distillation, and model compression techniques Location & Travel • This role is based in Irvine, CA • Hybrid work model: in-office 1-2 days per week required • Occasional travel to deployment sites or test locations may be needed