Software Engineer (Synthetic Data)

V7 At V7 we’re building AI platforms that help humans do their best work at incredible scale and speed.

Our mission is to turn human knowledge into trustworthy AI making complex tasks faster smarter and more accurate.

We’re growing fast backed by leading investors and AI pioneers (including the minds behind Transformers and Gemini).

THE TEAM YOU'LL BE JOINING AND IMPACT YOU'LL HAVE - You'll join a high-impact research and engineering team developing large-scale synthetic data pipelines that power frontier AI models - Bridge the gap between cutting-edge research and production systems translating experimental insights into scalable infrastructure - Work directly on training data that shapes the next generation of multimodal AI capabilities - Collaborate with researchers and ML practitioners who care deeply about both scientific rigor and real-world impact WHAT YOU'LL BE DOING FROM DAY ONE: - Design and maintain modular synthetic data generation pipelines for multimodal training tasks using proxy metrics and statistical experiments to validate output quality - Own end-to-end LLM experiments—from prompt engineering to reproducible evaluation—accelerating iteration with modern AI tooling like Cursor and GitHub Copilot - Build rigorous evaluation frameworks that assess pipeline performance through sound experimental design and clear statistical reasoning - Translate research breakthroughs into production-ready systems working across the stack with researchers and engineers to scale what works WHO YOU ARE - You have 3+ years of software engineering experience (Python or JavaScript preferred) and an MS+ in Computer Science Engineering Mathematics or related field with strong foundations in statistics and experimental design - You're fluent in LLM systems—from context engineering to output optimization—and stay current with research on training datasets and evaluation benchmarks (ChartQA ChartGalaxy synthetic data techniques) - You're comfortable with data infrastructure: Git DVC shell environments and pipeline orchestration are second nature to you - You thrive in ambiguity with a bias toward action viewing iteration and feedback as catalysts for discovery rather than setbacks while maintaining scientific rigor in both code and evaluation V7 champions equality and inclusion because diverse teams build better products.

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