Backend Software Engineer
Fireworks AI
Backend Software Engineer
Fireworks AI
AI inference platform for model deployment
Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
Here at Fireworks, we’re building the future of generative AI infrastructure. Fireworks offers the generative AI platform with the highest-quality models and the fastest, most scalable inference. We’ve been independently benchmarked to have the fastest LLM inference and have been getting great traction with innovative research projects, like our own function calling and multi-modal models. Fireworks is funded by top investors, like Benchmark and Sequoia, and we’re an ambitious, fun team composed primarily of veterans from Pytorch and Google Vertex AI.
As a Backend Software Engineer, you’ll be responsible for designing and developing the core backend systems that power Fireworks AI’s high-performance generative AI platform. Your work will focus on ensuring efficiency, scalability, and stability in handling AI workloads.
Design and build core backend software components, ensuring efficiency, scalability, and stability of system resources
Conduct design/code reviews and collaborate with cross-functional teams
Continuously analyze and optimize infrastructure efficiency for AI workloads (compute, storage, networking)
Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
3+ years experience working in ML infra (PyTorch, Vertex AI, Sagemaker, etc.)
Experience building, scaling, and optimizing enterprise-grade Machine Learning systems
Experience in AI or large scale infrastructure
Master’s or PhD degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
AI inference platform for model deployment
Fireworks AI provides an AI inference platform that helps organizations run, customize, and deploy machine learning models. It supports deployment, fine-tuning, and inference workflows, with access to open-source models and on-demand deployment options through a subscription model. The platform enables users to configure and optimize models for production environments, manage variants, and scale AI workloads while controlling costs. Unlike some competitors, the emphasis is on end-to-end production-grade inference and fine-tuning across a range of clients, from tech firms to research institutions and enterprises, with tools tailored for rapid deployment and cost efficiency. The long-term goal is to expand the use of AI in production by building compound AI systems, growing the team, and delivering broader platform capabilities that accelerate AI adoption in real-world settings.
Explore more opportunities at Fireworks AI