Fireworks AI

Own Fireworks’ DevOps automation layer, delivery infrastructure, and API integrations supporting billions of daily AI requests. You’ll build resilient workflows and self-healing systems using tools such as n8n, Python, Terraform, Kubernetes, and cloud platforms.

Join Fireworks as a 2026 PhD new graduate building the scheduling, storage, caching, and networking systems that power large-scale AI training and inference. You’ll turn systems research into production infrastructure running across fleets of tens of thousands of accelerators.

Join Fireworks as an Applied Machine Learning Engineer building, fine-tuning, and deploying AI systems for real customers. This new-grad role combines hands-on ML engineering, customer-facing proof-of-concepts, and contributions to a production ML platform.

Build production AI infrastructure and product capabilities for Fireworks’ EMEA field team, spanning inference, model serving, fine-tuning, and post-training tooling. This flexible role is designed for exceptional software engineers with 3–10 years of experience.

Own reliability across Fireworks AI’s cloud and AI infrastructure, from SLOs and observability to incident response, failure testing, and automation. You’ll solve cross-system production problems and make high-throughput AI systems dependable at scale.

Own foundational enterprise capabilities that let large customers securely run Fireworks in production, spanning backend systems, identity, authorization, billing, encryption, and cloud deployment. You’ll turn customer and security requirements into end-to-end features that operate safely across live AI infrastructure.

Build and own end-to-end AI developer products for Fireworks Nexus, including intelligent routing, integrations, observability, APIs, and enterprise controls. This high-autonomy role combines React and TypeScript frontend work with Python and Go backend development for technical users.

Build the distributed infrastructure that powers large-scale LLM and multimodal model training. You’ll work with AI researchers and engineers to optimize GPU-based training systems, pipelines, storage, and orchestration.