QA Implementation Specialist | Vision AI Products at Distro

QA Implementation Specialist \u007C Vision AI Products Build the future of multi-site video with us At Savi, our mission is to make Main Street smarter by unlocking the power of video data for multi-site operators. We deliver AI-driven insights that help restaurant and retail teams improve operations, increase revenue, and create better customer experiences. We’re looking for a QA Implementation Specialist to bridge product development and customer implementation. This hybrid role sits primarily in the product development department, testing and providing insightful summaries of new feature performance. The specialist will also work in operations to implement these new products for customers. We seek someone who can build out our processes to help transition implementations to the operations team as features mature and scale. What you’ll do: • Operate across two core areas: Product QA and Customer Implementation. Product Development QA: • Test new AI features prior to release to ensure accuracy and reliability. • Evaluate outputs from computer vision models and analytics pipelines. • Identify and document edge cases, failure modes, and inconsistencies. • Quantify performance using structured validation (e.g., accuracy checks, pattern analysis). • Partner with engineering to triage issues and drive iterative improvements. • Provide clear, actionable feedback to improve model performance and product quality. Example: For a feature detecting employee entry/exit events, you would review results across scenarios, measure accuracy, and document failures such as missed detections, false positives, and re-identification issues to inform engineering improvements. Customer Implementation & Validation: • Configure and deploy AI solutions for new customer locations. • Configure and deploy point-of-sale integrations. • Validate camera setups, configurations, and feature outputs for accuracy and readiness. • Perform end-to-end testing before customer handoff. • Identify and trace issues in live environments across hardware, video, data pipelines, and configurations. • Collaborate with engineering, product, and operations teams to resolve or independently fix issues. • Ensure a seamless transition to Customer Success with confident data quality. Example: After deploying an employee tracking feature, configure the system, validate detections, and confirm functionality before marking it ready for use. What we’re looking for: • High ownership; final owner of quality. • Technical background is a plus. • Strong systems thinking to understand interactions among hardware, software, and data pipelines. • Proven ability to identify root causes and resolve issues. • High attention to detail in validating data and video outputs. • Clear documentation and communication skills for both technical and non-technical teams. • Comfortable in a fast-paced, iterative environment. Bonus points: • Experience with computer vision systems (object detection, tracking, re-identification). • Familiarity with video analytics or AI-based products. • Experience with edge devices, cameras, or hardware deployments. • Experience analyzing structured data (CSV, JSON, SQL). • Exposure to QA processes, test planning, or validation frameworks. Location: • Hybrid / Remote #Savi #LI-PROMOTED #LI-Remote