Fireworks AI

Own the enterprise foundations that let major companies securely run AI workloads on Fireworks. You’ll build everything from core data models and APIs to authorization, billing, encryption, and customer-cloud deployments, with direct influence on enterprise deals and production systems.

Own and ship full-stack AI products for Fireworks Nexus, including intelligent model routing, developer integrations, cost observability, and enterprise controls. This high-autonomy Member of Technical Staff role is focused on turning complex AI infrastructure into polished products for technical users.

Build and optimize the distributed infrastructure powering Fireworks’ large-scale LLM and multimodal model training. You’ll work with AI researchers and engineers on scalable pipelines, performance optimization, orchestration, and reliable training operations.

Build and deploy production AI solutions that connect cutting-edge machine learning research with real customer needs. This hands-on role spans model enablement, application development, platform improvements, and customer-facing technical delivery.

Build and deploy production-grade GenAI systems directly with ambitious enterprise customers, from discovery and POCs through scale. This hands-on field role combines AI infrastructure engineering, model serving and fine-tuning with executive-level technical partnership.

Build and operationalize machine learning applications that solve real customer problems at Fireworks. This hands-on role combines AI engineering, model enablement, platform development, performance optimization, and customer-facing technical delivery.

Build and deploy production AI systems directly alongside ambitious enterprise customers across EMEA. This hands-on field role combines Python engineering, model serving, fine-tuning, performance optimization, and executive-level technical partnership.

Join Fireworks as a Research Engineer working at the intersection of machine learning research and distributed training infrastructure. You’ll design and extend advanced deep learning methods while building the systems needed to run them at massive GPU scale.