Software Engineer, LLM Infrastructure

Fireworks AI; New York (NY); On-site; USD 175,000 - 220,000; Full time

Benefits offered by this job

Equity

Competitive salary

Comprehensive benefits

Job summary

Fireworks AI is hiring a Software Engineer for its AI Infrastructure team to design and build core systems powering our generative AI platform. You will collaborate with cloud, product, and performance teams to deliver scalable infrastructure for training, inference, and data pipelines.

The role focuses on reliability, performance, and availability, with opportunities to influence architecture and tooling across the stack and to contribute to cutting‑edge ML infrastructure and open‑source

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
• 3 years of experience in software engineering, with a focus on infrastructure or machine learning systems
• Strong programming skills in Python, Go, or a similar language
• Proven experience in ML infrastructure and tooling (e.g., PyTorch, MLflow, Vertex AI, SageMaker, Kubernetes, etc.)
• Basic understanding of LLM knowledge (e.g., context length, disaggregated prefill, KV cache memory estimation)

Responsibilities

• Contribute to the design and development of scalable backend infrastructure that supports distributed training, inference, and data pipelines
• Build and maintain core backend services such as LLM CI/CD pipeline, control plane, and model serving systems
• Support performance optimization, cost efficiency, and reliability improvements across compute, storage, and networking layers
• Building frameworks and safeguards to ensure Fireworks AI has the best model quality in the industry
• Collaborate with performance, training, and product teams to translate research and product needs into infrastructure solutions
• Participate in code reviews, technical discussions, and continuous integration and deployment processes

Skills

Python

Go

ML infrastructure

LLM knowledge

Education

Bachelor’s degree in CS/Engineering or related field

Tools

PyTorch

MLflow

Vertex AI

SageMaker

Kubernetes

vLLM

Sglang

TRT-LLM

Job 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:

As a Software Engineer on our AI Infrastructure team, you will help design the core systems that power Fireworks AI’s generative AI platform. You will help build infrastructure and tools that ensure the reliability, performance, quality, and availability of our AI system.

Our mission is to make Fireworks AI the most reliable and user‑friendly generative AI platform in the world. You will partner closely with our cloud infrastructure team, product team, and performance team to deliver infrastructure that bridges the gap between our customer and the ultra‑performant proprietary Fireworks inference engine.

Key Responsibilities:

• Contribute to the design and development of scalable backend infrastructure that supports distributed training, inference, and data pipelines
• Build and maintain core backend services such as LLM CI/CD pipeline, control plane, and model serving systems
• Support performance optimization, cost efficiency, and reliability improvements across compute, storage, and networking layers
• Building frameworks and safeguards to ensure Fireworks AI has the best model quality in the industry
• Collaborate with performance, training, and product teams to translate research and product needs into infrastructure solutions
• Participate in code reviews, technical discussions, and continuous integration and deployment processes

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
• 3 years of experience in software engineering, with a focus on infrastructure or machine learning systems
• Strong programming skills in Python, Go, or a similar language
• Proven experience in ML infrastructure and tooling (e.g., PyTorch, MLflow, Vertex AI, SageMaker, Kubernetes, etc.).
• Basic understanding of LLM knowledge (e.g., context length, disaggregated prefill, KV cache memory estimation, etc)

Preferred Qualifications:

• 5+ years of experience in software engineering, with a focus on infrastructure or machine learning systems
• Experience with open source inference engine like vLLM, Sglang, or TRT‑LLM
• Contributions to open‑source infrastructure or ML projects
• Experience in building large‑scale ML/MLOps infrastructure

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.