Vivid Machines

Product Manager

• Own the full software product stack at Vivid Machines: the embedded camera software that runs on our hardware in the field, the mobile app used by operators during scanning, the grower-facing analytics dashboard, and the internal tools our team uses to manage deployments, data quality, and customer operations.
• Own and maintain the roadmap across the camera software, operator app, grower dashboard, and internal tools - balancing near-term commitments with longer-horizon platform investments.
• Write PRDs that are specific enough for engineering to build from: clear problem framing, measurable success criteria, explicit user stories, and right-sized scope.
• Define expansion priorities as we add new crops and geographies, working with agronomists and field teams to understand what changes technically and operationally.
• Surface product risks early - especially around ML model readiness, hardware dependencies, and seasonal deployment windows that constrain when we can ship and test.
• Play a key role in product marketing activities, from understanding markets to helping teams communicate about the product.
• Run the sprint process end to end: backlog grooming, story sizing, sprint planning, reviews, and retrospectives.
• Write acceptance criteria specific enough for engineering to build and QA to verify without ambiguity.
• Track sprint velocity, flag scope and timeline risks before they become blockers, and maintain a live view of what’s in flight, at risk, and next.
• Manage cross-functional dependencies between software, machine learning, and hardware or field operations so sprint outputs can actually be deployed and tested.
• Conduct regular discovery interviews with growers, orchard managers, and ag consultants — and translate what you hear into product requirements. This means you’ll be visiting farms.
• Participate in seasonal field deployments where possible; understand firsthand how our hardware and software performs in real orchard and vineyard conditions.
• Own the product roadmap for internal tooling used by our operations and data teams: deployment tracking, data quality tools, model feedback loops, and customer onboarding tools.
• Identify where manual internal processes can be productised, and work with engineering to scope and ship improvements that increase team efficiency.