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Fireworks is a Series D AI infrastructure platform enabling enterprises to build, train, and deploy specialized AI models tailored to their data and workflows. The company is backed by leading investors including NVIDIA, Sequoia, Benchmark, and others, and is valued at $17.5 billion.
As a Member of Technical Staff on the Research team, you will conduct foundational research to advance large language models and multimodal AI systems. Your focus will be on improving model efficiency, accuracy, and scalability through novel architectures, training methodologies, and optimization techniques. You'll work at the intersection of cutting-edge research and production systems, collaborating with deep learning experts and distributed systems engineers to transition research prototypes into real-world applications.
Key responsibilities include designing and evaluating novel model architectures and training methods, analyzing empirical results to identify performance bottlenecks, and iterating rapidly to improve model quality. You'll also contribute to internal research strategy by identifying high-impact opportunities and emerging trends in generative AI. Your work will directly shape how leading companies globally build and deploy AI systems.
You should have a research background in AI, machine learning, physics, or a related field, with strong analytical and quantitative problem-solving skills. Proficiency in C/C++, Python, or similar languages is required. A PhD in Computer Science, Computational Physics, Mathematics, or related discipline is preferred. Prior research experience demonstrated through publications, grants, fellowships, or patents is highly valued. Familiarity with ML frameworks like PyTorch, TensorFlow, or JAX is a plus.
This is an opportunity to work on hard problems at the frontier of AI infrastructure, from low-latency inference to scalable model serving, alongside world-class researchers and engineers in a fast-growing, collaborative environment.
