Director of Voice AI

Motorola Solutions • Vancouver, BC

1d • CA$220,000 - CA$250,000 • Remote

About The Position

Motorola Solutions' innovations, products, and services play essential roles in people's lives. Our end-to-end suite of software solutions helps customers manage emergency communications, process video and evidence, and leverage cutting-edge AI-driven analytics for security and operational insights. We are industry leaders in video security and analytics, with solutions deployed in more than 120 countries across diverse environments such as school campuses, transportation systems, healthcare centers, public venues, critical infrastructure, prisons, factories, casinos, airports, financial institutions, government facilities, and retailers. Our AI-powered security solutions integrate advanced video analytics, machine learning, and embedded intelligence to enable proactive threat detection, enhanced situational awareness, and automated decision-making. Reporting to the VP of AI for Motorola Solutions, the Director of Voice AI will be a critical, high-impact executive leader who thrives on turning highly ambiguous concepts into enterprise-scale Voice AI solutions. They will lead a unified, world-class research and engineering organization responsible for the end-to-end lifecycle of Voice AI technologies—spanning from ML research to large-scale production deployment. This role is responsible for defining the technical vision, bridging the gap between cutting-edge AI research and robust product engineering, and ensuring the execution and robust delivery of next-generation voice intelligence solutions across Motorola’s product portfolio.

Requirements

• 10+ years of technical leadership experience leading Voice AI and Speech Technology teams and organizations, with a focus on building and deploying enterprise-scale platforms and solutions in production.
• Deep, demonstrable expertise in Voice AI (e.g., ASR, NLU, LLMs), machine learning algorithms, and the end-to-end MLOps lifecycle, including 5+ years of hands-on experience building and optimizing Voice AI models (e.g., ASR/NLU/TTS systems) or as a Voice AI researcher.
• Proven ability to engage in complex technical discussions, define the architectural vision for central, reusable AI infrastructure and models, and drive technical strategy while managing critical trade-offs.
• Proven experience defining long-term technical vision, engineering strategy, and roadmaps for a large-scale platform.
• Expertise in defining and implementing technical metrics (e.g., latency, throughput, system reliability, model efficiency) to measure engineering excellence and drive continuous improvement across an organization.
• Demonstrated ability to manage and scale a unified, distributed engineering and research organization of 30 to 50 people, mentor senior technical talent, and lead multiple teams across different geographies.
• Hands-on experience driving innovation through foundational research, working with AI performance metrics (e.g., Precision/Recall), real-time audio/speech processing, and inference optimization.
• Track record of translating highly ambiguous product concepts and complex customer needs into clear, executable technical roadmaps and architectural specifications.
• Experience in a start-up or fast-paced environment is highly valued, demonstrating high ownership, bias for action, comfort with ambiguity, and the ability to drive 0-to-1 product development with limited resources.
• Bachelors degree with 10+ years of technical leadership experience leading Voice AI and Speech Technology teams and organizations AND 5+ years of hands-on experience building and optimizing Voice AI models (e.g., ASR/NLU/TTS systems) or as a Voice AI researcher.

Nice To Haves

• Experience in public safety, security-focused software (e.g., speech analytics, real-time dispatch management), mission-critical systems, or emergency communications is a plus, building enterprise-scale voice assistants and/or AI agents, and a deep understanding of hybrid cloud/edge architecture, including the trade-offs for deploying voice AI models on edge devices versus cloud environments.

Responsibilities

• Define the long-term research agenda for fundamental Voice AI and speech capabilities and drive the culture of scientific excellence.
• Provide executive technical leadership to a unified research and engineering organization, defining the technical architecture, strategy, and engineering roadmap for the Voice AI Platform.
• Drive execution, ensuring the seamless translation of product requirements into robust technical specifications and successful delivery of next-generation voice intelligence solutions that are highly scalable and align with overall product and business strategy.
• Manage and scale a unified Voice AI research and engineering organization distributed across multiple geographies, overseeing multiple teams, and defining the strategy for recruiting, mentoring, and attracting world-class talent.
• Own the entire engineering lifecycle for central, reusable Voice AI models and foundational AI infrastructure. This includes establishing best-in-class MLOps practices for scalable training, efficient deployment, continuous monitoring, and performance optimization across edge and cloud environments.
• Define, implement, and track key technical performance metrics (e.g., latency, throughput, model efficiency, system reliability) to measure engineering success, identify bottlenecks, and drive continuous improvement in execution and delivery.
• Evaluate and integrate cutting-edge Voice AI research and technologies.
• Proactively identify and mitigate significant technical risks, and lead critical engineering decisions, including build-versus-buy analysis.

Benefits

• We are committed to providing an inclusive and accessible recruiting experience for candidates with disabilities, or other physical or mental health conditions.

What This Job Offers

• Job Type: Full-time
• Career Level: Executive