Member of Technical Staff, Software Engineer at Fireworks AI

San Mateo, California, United States -

Full Time

Start Date

Immediate

Expiry Date

28 Jun, 26

Salary

220000.0

Posted On

30 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Backend Systems, Infrastructure, Distributed Systems, APIs, Web Backend, Developer Tooling, Model Training, Inference Orchestration, Job Scheduling, Autoscaling, Model Serving, Cloud Infrastructure, GPU Cluster Management, System Design, Performance Optimization, Cost Optimization

Industry

Software Development

Description

About Us: At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI. The Role You’ll help build the core systems powering Fireworks AI — from customer-facing APIs and product features to the distributed infrastructure running AI workloads at scale. This is a true full-stack backend + infra role. You’ll design systems, ship product, and own everything end-to-end, not just tickets. What You’ll Work On APIs, web backend, and developer tooling Model training, fine-tuning, and inference orchestration Job scheduling, autoscaling, and model serving Billing, enterprise features, and access control Cross-cloud infrastructure (compute, storage, networking) Global scale GPU cluster management What You’ll Do Build and scale backend services and distributed systems Own systems from design → production → reliability Work directly with customers to solve real problems Optimize performance, cost, and developer experience Move fast and use AI tools to automate everything you can You Might Be a Fit If You cannot wait to jump into the forefront of AI revolution You like to build infrastructure and backend that are directly contributing to products You think in systems, tradeoffs, and impact You take ownership and drive things across teams Requirements 5+ years building backend or infrastructure systems Strong distributed systems fundamentals Experience with cloud (AWS/GCP/Azure) Familiar with ML/AI tooling or platforms Comfortable working with both humans and AI systems Bonus Experience with large-scale ML infrastructure Kubernetes / cloud-native stack Infra-as-code, CI/CD, or open-source contributions 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) $175,000—$220,000 USD 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. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

Responsibilities

The role involves building and scaling core backend services and distributed systems that power the Fireworks AI platform, ranging from customer-facing APIs to large-scale AI workload infrastructure. Responsibilities include owning systems end-to-end from design through production and reliability, optimizing performance, and working directly with customers.