Member of Technical Staff, LLM Infrastructure
Join Fireworks AI as a Software Engineer to design and build scalable infrastructure for generative AI systems.
Posted by employer 11 months ago
First seen on Joblaze 3 months ago
Last verified on the company career page 6 hours ago
AI in the day-to-day
Engineers will help build infrastructure and tools that ensure the reliability, performance, quality, and availability of our AI system.
Requirements
- Experience
- 3–5 years
- Education
- Bachelor's degree
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
In this role, the Software Engineer will focus on designing and developing the backend infrastructure that supports Fireworks AI's generative AI platform, ensuring its reliability and performance. Key skills include strong programming in Python or Go and experience with machine learning infrastructure tools like PyTorch and Kubernetes. This position is ideal for candidates with at least three years of experience in software engineering, particularly those with a background in infrastructure or machine learning systems. Fireworks AI offers a dynamic environment where engineers can tackle complex challenges and collaborate with leading experts in the field.
Joblaze insights
Quick facts
- How much experience is required?
- 3–5 years of relevant experience for this Member of Technical Staff, LLM Infrastructure role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Go, Kubernetes, MLflow, PyTorch, Python, Sagemaker.
- What seniority level is this role?
- Fireworks AI targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Member of Technical Staff, LLM Infrastructure role at Fireworks AI.
From the original posting
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
Why Fireworks?
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Standard company text repeated across Fireworks AI's postings is omitted here.