Member of Technical Staff, AI Training Infrastructure

The role

You will design, build, and optimize infrastructure for large-scale model training operations. You will collaborate with AI researchers to create training pipelines and optimize distributed training workloads.

What you will do

• 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

Required qualifications

• 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 PyTorch
• Proficiency in cloud platforms (AWS, GCP, Azure)
• Experience with containerization, orchestration (Kubernetes, Docker)
• Knowledge of distributed training techniques (data parallelism, model parallelism, FSDP)

Nice to have

• 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 DevOps practices
• Contributions to open-source ML infrastructure or related projects

About the company

Fireworks is a platform for specialized intelligence that enables companies to build, train, and serve AI models. It is a Series D company valued at $17.5 billion.