Wizard

Account Manager

• Identify and prioritize high-value merchants aligned to Wizard’s consumer demand, category strategy, and coverage gaps
• Build and manage a high-velocity pipeline (sourcing, outreach, multi-threading, stakeholder mapping, next steps, and close plans)
• Lead discovery and pitch Wizard’s value proposition; drive deals from first meeting through signature
• Negotiate launch-ready partnership agreements covering commercial economics, including affiliate and/or direct terms, product feed requirements, reporting expectations, and onboarding scope, while partnering with Product and Engineering to validate native checkout requirements and technical feasibility.
• Own internal deal process: pricing/terms alignment, approvals, and contract readiness (partnering with Legal as needed)
• Partner closely with Product, Engineering, Merchant Success, and Merchant Operations to define realistic integration and onboarding pathways, set clear expectations with merchants, and ensure clean launch-ready handoff.
• Develop and continuously improve Wizard’s merchant acquisition process, including Tier-1 vs. Tier-2 playbooks, qualification criteria, outreach templates, pipeline reporting, and weekly funnel health tracking across volume, stage conversion, and forecast.
• Develop repeatable acquisition channels across outbound prospecting, partner referrals, approved commerce/integration partners, and industry events, with a focus on generating qualified merchants that can launch quickly and monetize effectively.
• Coordinate with approved merchant onboarding partners to identify qualified merchant opportunities, accelerate handoffs, and improve the efficiency of Wizard’s acquisition motion.

Business Development Manager, Merchant Partnerships

Machine Learning Engineer

• Own and evolve our multi-engine inference platform, supporting a variety of model types and serving requirements.
• Build and improve production ML pipelines — taking models from experimentation to reliable, high-throughput serving.
• Define and implement model versioning, rollout, rollback, and lifecycle management strategies that ensure reproducibility and operational reliability.
• Define and enforce serving-layer SLAs, including latency, availability, GPU utilization, Time-to-First-Token (TTFT), and Inter-Token Latency (ITL).
• Build observability, monitoring, alerting, and operational tooling for production inference systems.
• Apply software engineering best practices, including testing, CI/CD integration, and reproducibility across ML workflows.
• Optimize inference performance through efficient resource utilization, hardware-aware serving strategies, and cost-conscious infrastructure design.
• Ensure ML serving systems are secure, scalable, and operationally resilient.
• Partner with ML, Data, Product, and DevOps teams to turn ideas into production systems, driving the technical decisions on serving and scale.

Business Development Manager, Merchant Partnerships

Senior Machine Learning Engineer – Inference Platform