Jobs at Wyze

Own product strategy and execution for Wyze’s Never Wonder initiative, transforming smart-home data into personalized AI-driven insights and recommendations. The role translates concepts into requirements, milestones, features, experiments, and launches; collaborates with engineering, design, research, hardware, software, and leadership; uses customer feedback and metrics to prioritize improvements; and independently drives cross-functional delivery in an ambiguous, fast-moving environment.

Manage and grow emerging retail accounts while developing new specialty retail, B2B distribution, builder, developer, and other channel partnerships. Responsibilities include prospecting, relationship management, account planning, negotiations, promotional planning, demand forecasting, profitability analysis, and performance improvement. The role owns partnerships from initial outreach through launch and ongoing growth, working cross-functionally with supply chain, marketing, finance, product, and business intelligence teams.

Build secure-by-default infrastructure platforms, policy-as-code guardrails, identity and access automation, and automated security and compliance controls. Develop reusable infrastructure patterns, self-service workflows, CI/CD and GitOps protections, least-privilege enforcement, and continuous compliance capabilities. Detect configuration drift and automate remediation across cloud environments and engineering workflows while collaborating with teams across the organization.

Lead a zero-to-one consumer product (Never Wonder) converting smart-home data into AI-driven insights. Define vision, roadmap, UX flows, and metrics; lead cross-functional teams (engineering, AI/ML, design, data); drive discovery, prototyping, launch, iteration, and go-to-market readiness.

Lead S&OP and inventory planning to balance demand, supply, service levels, and working capital. Improve planning systems, build analytical algorithms and AI-enabled workflows, manage overseas suppliers, and lead a supply chain analytics team to drive data-driven inventory decisions and presentations to leadership.

Develop and deploy in-house vision-language models for smart home video understanding: track research, train and evaluate multimodal VLMs on large-scale video data, design evaluation pipelines, build prototypes, inform product direction, and publish or open-source research.