Jobs at Fireworks AI Current Openings Shape the Future of Generative AI At Fireworks AI, we’re building the infrastructure that powers the next generation of AI applications. From real-time inference to model optimization, our platform empowers developers and enterprises to deploy, scale, and innovate with cutting-edge AI—faster and smarter than ever before. Why Fireworks AI? 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. We’re seeking builders, tinkerers, and visionaries who: 🚀 Push boundaries in AI/ML infrastructure, distributed systems, or high-performance computing. 💡 Think creatively to solve problems others deem impossible. 🤝 Collaborate fearlessly in a fast-paced, no-ego environment. 🌍 Care deeply about democratizing AI and making it accessible, scalable, and efficient. Frequently Asked Questions: How can I learn more about the Fireworks AI team? Our team brings decades of AI experience from major tech titans. You can learn more about the co-founders here ! If you’re excited to solve problems that redefine how AI is built and deployed, we’d love to hear from you. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators. Create a Job Alert Level-up your career by having opportunities at Fireworks AI sent directly to your inbox. Create alert Featured Jobs Member of Technical Staff, Performance Optimization San Mateo, CA $175,000 - $220,000 USD
The Role: We're looking for a Software Engineer focused on Performance Optimization to help push the boundaries of speed and efficiency across our AI infrastructure. In this role, you'll take ownership of optimizing performance at every layer of the stack—from low-level GPU kernels to large-scale distributed systems. A key focus will be maximizing the performance of our most demanding workloads, including large language models (LLMs), vision-language models (VLMs), and next-generation video models. You’ll work closely with teams across research, infrastructure, and systems to identify performance bottlenecks, implement cutting-edge optimizations, and scale our AI systems to meet the demands of real-world production use cases. Your work will directly impact the speed, scalability, and cost-effectiveness of some of the most advanced generative AI models in the world. Key
Responsibilities: Optimize system and GPU performance for high-throughput AI workloads across training and inference Analyze and improve latency, throughput, memory usage, and compute efficiency Profile system performance to detect and resolve GPU- and kernel-level bottlenecks Implement low-level optimizations using CUDA, Triton, and other performance tooling Drive improvements in execution speed and resource utilization for large-scale model workloads (LLMs, VLMs, and video models) Collaborate with ML researchers to co-design and tune model architectures for hardware efficiency Improve support for mixed precision, quantization, and model graph optimization Build and maintain performance benchmarking and monitoring infrastructure Scale inference and training systems across multi-GPU, multi-node environments Evaluate and integrate optimizations for emerging hardware accelerators and specialized runtimes Minimum
Qualifications: Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience 5+ years of experience working on performance optimization or high-performance computing systems Proficiency in CUDA or ROCm and experience with GPU profiling tools (e.g., Nsight, nvprof, CUPTI) Familiarity with PyTorch and performance-critical model execution Experience with distributed system debugging and optimization in multi-GPU environments Deep understanding of GPU architecture, parallel programming models, and compute kernels Preferred
Qualifications: Master’s or PhD in Computer Science, Electrical Engineering, or a related field Experience optimizing large models for training and inference (LLMs, VLMs, or video models) Knowledge of compiler stacks or ML compilers (e.g., torch.compile, Triton, XLA) Contributions to open-source ML or HPC infrastructure Familiarity with cloud-scale AI infrastructure and orchestration tools (e.g., Kubernetes) Background in ML systems engineering or hardware-aware model design Example projects: Implement fully asynchronous low-latency sampling for large language models integrated with structured outputs Implement GPU kernels for the new low-precision scheme and run experiments to find optimal speed-quality tradeoff Build a distributed router with a custom load-balancing algorithm to optimize LLM cache efficiency Define metrics and build harness for finding optimal performance configuration (e.g. sharding, precision) for a given class of model Determine and implement in PyTorch an optimal sharding scheme for a novel attention variant Optimize communication patterns in RDMA networks (Infiniband, RoCE) Debug numerical instabilities for a given model for a small portion of requests when deployed at scale Search Department Select... Office Select... 29 jobs Engineering Job Applied Machine Learning Engineer New York, NY; San Mateo, CA IT Engineer San Mateo, CA Member of Technical Staff, AI Training Infrastructure San Mateo, CA Member of Technical Staff, Cloud Infrastructure New York, NY; San Mateo, CA Member of Technical Staff, Cluster Management San Mateo, CA Member of Technical Staff, Data Platform Engineer San Mateo, CA Member of Technical Staff, Evals & Post-Training Product San Mateo, CA Member of Technical Staff, Performance Optimization San Mateo, CA Member of Technical Staff, Research San Mateo, CA Member of Technical Staff, Software Engineer San Mateo, CA Security Engineer San Mateo, CA Software Engineer, AI Infrastructure New York, NY; San Mateo, CA Solutions Architect New York, NY; San Mateo, CA Support Engineer San Mateo, CA G&A Job Executive Assistant - Senior Leadership Team San Mateo, CA G&A HR Job People Operations Lead San Mateo, CA G&A Recruiting Job Senior GTM Recruiter New York, NY; San Mateo, CA Senior Recruiter San Mateo, CA Go To Market Job AI Native Account Executive New York, NY; San Mateo, CA Business Development Representative (BDR) San Mateo, CA Enterprise Account Executive New York, NY; San Mateo, CA Go-To-Market Operations Manager San Mateo, CA Go To Market Partnerships Job Head of Microsoft Partnership Remote, USA; San Mateo, CA Marketing Job Sr Field Marketing Manager (West) San Mateo, CA Technical Developer Advocate New York, NY; San Mateo, CA Product Job Associate Product Manager San Mateo, CA Forward Deployed Product Manager San Mateo, CA Product Designer San Mateo, CA Strategic Projects Lead San Mateo, CA Powered by Greenhouse
About Fireworks AI
Fireworks is the fastest way to build, tune, and scale AI on open models. Ship production-ready AI in seconds on our globally distributed cloud infrastructure, optimized for your use case. Fireworks powers production workloads at companies like Uber, Doordash, Notion, and Cursor—delivering 15× faster speed, 4× lower latency, and 4× more concurrency than closed models.
