Teams at SPREEAI

Supports partnership prospecting, high-volume outreach, CRM management, partner account communications, onboarding, demo creation, quality assurance, event execution, and cross-functional partnership initiatives. The role manages pipeline reporting, coordinates with product and engineering teams, and helps drive partner acquisition and revenue growth in a remote startup environment.

Build and operate scalable AI infrastructure for multimodal model training and inference. Responsibilities include developing model-serving APIs, distributed GPU systems, backend services, deployment automation, observability, reliability improvements, and performance and cost optimization. The engineer will partner with applied science teams to productionize generative and vision models while improving platform usability and scalability.

Lead the design and operation of SPREEAI’s ML platform, including training workflows, model deployment, inference serving, GPU infrastructure, observability, evaluation, and production monitoring. Establish reliable research-to-production pipelines, model governance, SLOs, rollback strategies, and performance optimization across distributed systems. Partner with research, product, and engineering teams to deliver scalable, cost-efficient multimodal AI systems for real-time virtual try-on experiences.