Member of Technical Staff, AI Training Infrastructure

The Role

As a Training Infrastructure Engineer, you'll design, build, and optimize the infrastructure that powers our large-scale model training operations. Your work will be essential to developing high-performance AI training infrastructure. You'll collaborate with AI researchers and engineers to create robust training pipelines, optimize distributed training workloads, and ensure reliable model development.

• Design and implement scalable infrastructure for large-scale model training workloads

• Develop and maintain distributed training pipelines for LLMs and multimodal models

• Optimize training performance across multiple GPUs, nodes, and data centers

• Implement monitoring, logging, and debugging tools for training operations

• Architect and maintain data storage solutions for large-scale training datasets

• Automate infrastructure provisioning, scaling, and orchestration for model training

• Collaborate with researchers to implement and optimize training methodologies

• Analyze and improve efficiency, scalability, and cost-effectiveness of training systems

• Troubleshoot complex performance issues in distributed training environments

• Bachelor's degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience

• 3+ years of experience with distributed systems and ML infrastructure

• Experience with Py Torch

• Proficiency in cloud platforms (AWS, GCP, Azure)

• Experience with containerization, orchestration (Kubernetes, Docker)

• Knowledge of distributed training techniques (data parallelism, model parallelism, FSDP)

• Master's or PhD in Computer Science or related field

• Experience training large language models or multimodal AI systems

• Experience with ML workflow orchestration tools

• Background in optimizing high-performance distributed computing systems

• Familiarity with ML Dev Ops practices

• Contributions to open-source ML infrastructure or related projects

• 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.