Director of Product, AI, Evolv Technology

• 8+ years of product management experience, including ownership of AI, machine learning, or computer vision products from strategy through production
• Experience bringing AI or computer vision systems to production in security, safety-critical, or other detection applications where accuracy and reliability matter
• Strong understanding of AI and computer vision architectures, model evaluation, data pipelines, and technical trade-offs
• Experience defining data collection, annotation, validation, and dataset quality standards
• Experience deploying and improving ML systems on physical or edge hardware
• Track record of leading cross-functional decisions across research, engineering, field operations, legal, and customer-facing teams
• Ability to translate technical complexity and business constraints into clear product decisions and priorities
• Experience designing field trials and using customer and performance data to inform product and release decisions

Desirable

• Evolv Technology is looking for a Director of Product, AI, a senior individual contributor who will work at the center of our AI engineering and research teams to build the industry's best weapons detection and computer vision capabilities
• You will get deep into the mechanics of how we collect data, define annotation standards, evaluate models, run field trials, and deploy detection systems into the real world, translating that work into product decisions to keep people safe
• You will embed directly with AI engineering as the product lead for our detection capabilities, operating with the technical depth to make and defend decisions about data, models, and evaluation methodology
• In the first 30 days, you will: Pressure-test how we collect data, set annotation standards, evaluate models, and run field trials. Come back with a sharp read on the biggest gaps, risks, and decisions, and a plan to move on them
• Within 90 days, you will: Ship a prioritized data collection strategy across the scenarios and threats that matter most. Lock annotation, dataset quality, and validation standards with AI engineering. Define the release-readiness bar, including accuracy, false positive/negative rates, latency, throughput, and real-world load, then get alignment on it. Turn field-trial results into real product and model decisions. Build the operating cadence and decision framework that keeps detection performance moving
• Within 6 months, you will: Own detection. You're the accountable product lead driving data priorities, model evaluation, release readiness, trade-offs, in lockstep with AI engineering and research. Shape the roadmap, balancing performance against latency, compute cost, hardware limits, and customer experience. Make sure every external claim about detection performance is accurate and defensible, and push hard with legal and compliance to get there
• By the end of the first year, you will: Demonstrate measurable improvement in detection performance and release predictability across priority use cases. Show that the operating mechanisms you established are consistently identifying performance gaps, driving timely decisions, and improving deployed models. Influence the longer-term detection roadmap through clear evidence about customer needs, technical trade-offs, and business impact
• AI/ML Lifecycle Ownership
• Define data collection strategy: what scenarios, environments, and threat types need more or better training data
• Own annotation guidelines in partnership with AI engineering
• Partner with AI engineering on training methodology and validation approach
• Define and own model evaluation metrics specific to weapons detection (false positive/negative rates, detection latency, throughput under real-world load) and the standards for when a model is ready to ship
• Design and run field trials with prospects and customers; use real-world trial results for product iteration
• Product & Technical Strategy
• Collaborate closely with AI researchers and engineers to define product vision and technical roadmaps
• Evaluate diverse AI models and technical approaches to select the optimal solution for specific security challenges
• Analyze trade-offs across latency, accuracy, compute cost, and hardware constraints, and make explicit decisions
• Oversee feature development from early experimentation through full production deployment
• Work with design and product teams to integrate AI capabilities into intuitive customer- and operator-facing workflows
• Partner with legal/compliance on how detection performance is represented externally to customers and the market
• You will report directly to the Chief Product Officer and operate as an individual contributor within the Product organization. This role will work closely with cross-functional partners and require travel to customer sites and field-trial locations to gather insights, support testing, and help translate real-world needs into product decisions