Member of Technical Staff, AI Training Infrastructure

SupportFinity™; San Francisco (CA); On-site; USD 175,000 - 220,000; Full time

Benefits offered by this job

Meaningful equity

Competitive salary

Comprehensive benefits package

Job summary

Fireworks AI is seeking a Member of Technical Staff to design, build, and optimize AI training infrastructure for large-scale models. You’ll collaborate with researchers to create high-performance training pipelines, scale workloads across GPUs and data centers, and implement robust monitoring and storage solutions for massive datasets.

You will contribute to distribution strategies (data/model parallelism, FSDP) and drive automation to improve efficiency, cost, and reliability of training

Qualifications

• Bachelor's degree 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).

Responsibilities

• Design and build 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.

Skills

Distributed systems

ML infrastructure

PyTorch

Cloud platforms

Kubernetes

Docker

Data parallelism

Model parallelism

FSDP

Education

Bachelor's degree in CS/CE or related field

Master's or PhD (preferred)

Tools

Docker

Kubernetes

Job description

Member of Technical Staff, AI Training Infrastructure

Fireworks AI |

Fireworks AI | Posted Mar 12

Full-time

Unknown

Negotiable

About Us

At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.

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.

Key Responsibilities

• 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

Minimum 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)

Preferred Qualifications

• 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

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.

Base Pay Range (Plus Equity)

$175,000 - $220,000 USD

Why Fireworks AI?

• 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.

About the company

Fireworks AI