AI Infrastructure Engineer, Model Serving Platform

On-site in San Francisco, CA or New York, NY. Full-time.

About Us

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force.

About the role

As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments. The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.

Responsibilities

• Build and maintain fault-tolerant, high-performance systems for serving LLMs workloads at scale.
• Build an internal platform to empower LLM capability discovery.
• Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
• Conduct architecture and design reviews to uphold best practices in system design and scalability.
• Develop monitoring and observability solutions to ensure system health and performance.
• Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment.

Requirements

• 4+ years of experience building large-scale, high-performance backend systems.
• Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
• Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.)
• Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc.
• Experience with containers and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to Haves

• Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.

Benefits

• Comprehensive health, dental and vision coverage.
• Retirement benefits.
• A learning and development stipend.
• Generous PTO.
• This role may be eligible for additional benefits such as a commuter stipend.

Pay

The base salary range for this full-time position in San Francisco, New York, or Seattle is $180,000—$225,000 USD. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale. It will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity-based compensation, subject to Board of Director approval.