Member of Technical Staff, AI Training Infrastructure

Member of Technical Staff, AI Training Infrastructure

San Mateo, CA

Fireworks is building the future of generative AI infrastructure. Our platform delivers high-quality models with scalable inference and fast performance. We are a Series C company valued at $4 billion, backed by investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. Our team includes veterans of Meta PyTorch and Google Vertex AI.

As a Training Infrastructure Engineer, you ll design, build, and optimize the infrastructure that powers our large-scale model training operations. You will 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

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.

$175,000 - $220,000 USD

• Solve Hard Problems:
  Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
• Build What  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.