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The Software Engineer will design and optimize large-scale data infrastructure, focusing on distributed systems and data processing for generative media models, collaborating closely with research scientists and enhancing multi-modal training pipelines.

Responsible for managing enterprise sales cycles, building relationships with key decision-makers, and developing sales strategies for AI-native design solutions.

Build consumer-facing generative-AI products and backend infrastructure across the full stack. Design APIs and data models, optimize systems for scale, integrate AI workflows, ship features rapidly, and collaborate cross-functionally with product and design while owning outcomes.

Lead Ideogram's storytelling across social and product channels, working with CEO and cross-functional teams to turn launches, customer insights, and product moments into fast, authentic narratives. Create repeatable communication systems, write copy, shape landing pages, storyboard videos, and coordinate creators, designers, and external partners to build the brand.

Lead open-source ML initiatives by turning internal research into polished public tooling, managing GitHub/Hugging Face repos, building developer community, writing technical content, and collaborating with internal and external partners to drive adoption and reproducibility of models and code.

Build and operate distributed training and inference infrastructure for generative AI at scale. Design highly available Kubernetes/GCP clusters for GPU/TPU workloads, optimize inference pipelines, scale workers, deploy and troubleshoot Linux-based systems, and collaborate across teams with strong ownership.

Build and deploy generative ML features for Ideogram's app and API: fine-tune and ship models, design evaluations and datasets, run error analyses, monitor reliability, and collaborate with research, infra, product, and clients to meet quality, latency, and cost goals.