Software Engineer, Infrastructure [Early Career]

Position Overview

Fireworks is building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. Backed by top investors and valued at $4 billion, we are a collaborative team of ambitious builders led by veterans from Meta PyTorch and Google Vertex AI.

As a Software Engineer on the Infrastructure team, you will design and build core systems powering Fireworks AI’s generative AI platform. You will work on projects supporting distributed AI workloads across multiple cloud environments, creating tools and services to ensure our platform remains fast, reliable, and scalable. This is an exciting opportunity for a new graduate eager to grow in software engineering while working hands-on with infrastructure, distributed systems, and large-scale machine learning platforms.

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 job schedulers, autoscalers, resource managers, and model serving systems.
• Support performance optimization, cost efficiency, and reliability improvements across compute, storage, and networking layers.
• Collaborate with ML, DevOps, and product teams to translate research and product needs into infrastructure solutions.
• Learn and apply modern cloud technologies including Kubernetes, Ray, Kubeflow, and MLFlow.
• Participate in code reviews, technical discussions, and continuous integration and deployment processes.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• Strong programming skills in Python, C++, or a similar language.
• Solid understanding of computer systems concepts such as networking, storage, and distributed computing.
• Familiarity with cloud platforms like AWS, GCP, or Azure, and containerization tools like Docker or Kubernetes.
• Knowledge and interest in cloud infrastructure, distributed systems, and machine learning.

Preferred Qualifications

• 2+ years of relevant industry experience through internships, co-ops, or full-time employment.
• Experience with ML frameworks such as PyTorch, TensorFlow, Vertex AI, or SageMaker.
• Exposure to infrastructure-as-code and CI/CD tools such as Terraform, ArgoCD, or GitHub Actions.
• Contributions to open-source infrastructure or ML projects.
• Strong problem-solving skills and curiosity to learn new technologies.

Benefits & Perks

• Total Compensation includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by 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: $140,000—$150,000 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.
• Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.