Jobs at Fireworks AI
Must have skills
Good to have skills
About this Opportunity
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.
We're looking for a strong Backend Infrastructure Engineer to help accelerate our multimedia AI capabilities. You'll build and optimize the infrastructure powering state-of-the-art multimodal AI including vision-language models (VLMs), and speech AI models. You'll focus on achieving industry-leading latency and throughput across diverse multimedia workloads. You'll develop infrastructure for features like VLM fine-tuning, real-time voice processing pipelines, and model enablement on the latest hardware. You'll be instrumental in helping us capture significant ARR growth in the multimedia AI space while ensuring we deliver the fastest, most reliable multimodal platform in the market.
Collaborate with ML engineers and researchers to productionize models and support evolving multimedia capabilities
Identify, profile and address performance bottlenecks across the stack, from media preprocessing to vision/audio encoders to the core inference engine
Ensure high reliability, observability, and security across backend systems.
Own the enablement and optimization of new model releases, ensuring we consistently deliver the fastest implementations in the market.
Build and maintain performant APIs and services
Collaborate closely with customers and sales teams to implement custom features and optimizations that drive ARR growth
Propose new roadmap items based on customer needs.
Bachelor’s degree in Computer Science, Engineering, or a related field.
3+ years of experience as a backend or infrastructure engineer, ideally supporting ML/AI systems or data-intensive workloads.
Experience with PyTorch and deep learning frameworks for inference and training.
Strong programming skills in Python and/or Go, with a track record of building reliable distributed backend systems.
Experience with cloud platforms (e.g., AWS, GCP), infrastructure-as-code tools (e.g., Terraform), and containerization/orchestration tools (e.g., Docker, Kubernetes).
Experience supporting ML workloads in production (model fine-tuning, distributed training, inference optimization)
Experience working directly with LLMs, vision-language models, audio models (ASR, TTS) or other multimodal AI systems in production environments
Experience with performance optimization and profiling for high-throughput systems
Knowledge of model quantization, speculative decoding, or other ML optimization techniques
Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.
Base Pay Range (Plus Equity)
$170,000 - $240,000 USD
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.
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