Model Serving Engineer

About This Opportunity

We are representing a confidential technology client seeking a Model Serving Engineer to design, build, and operate high-performance inference platforms for serving large machine learning models in production environments. This is a 100% remote position available to candidates located anywhere in the United States.

This role focuses on the systems engineering side of AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads. Our client values strong distributed systems expertise and a proven track record shipping serving systems at scale.

Responsibilities

• Design and build high-performance, highly reliable inference platforms for large machine learning models
• Implement and optimize request routing, batching, caching, and autoscaling mechanisms
• Maximize GPU utilization and manage accelerator resources efficiently
• Develop end-to-end observability solutions including metrics, tracing, and structured logging
• Balance trade-offs between latency, throughput, cost, and quality in production ML serving
• Operate and maintain distributed systems at scale with strong incident response protocols
• Perform capacity planning and performance engineering for AI workloads
• Support external-facing AI APIs and ensure reliability across diverse model workloads

What We're Looking For

Required Qualifications:

• Bachelor's or Master's degree in Computer Science or related field
• 7+ years of experience in distributed systems, infrastructure, or ML platform engineering
• Strong proficiency in Python and a systems language such as Go, Rust, or C++
• Deep experience operating high-throughput, low-latency services in production
• Hands-on experience with LLM or large model inference frameworks such as vLLM or TensorRT-LLM
• Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization
• Familiarity with Kubernetes, autoscaling, and modern cloud platforms
• Experience with observability stacks including metrics, tracing, and structured logging
• Solid grounding in performance engineering and capacity planning
• Strong communication and incident response skills

Preferred Qualifications:

• Open-source contributions to model serving infrastructure
• Experience with multi-region or globally distributed AI serving
• Familiarity with model quantization, distillation, and compression techniques
• Exposure to FinOps for AI workloads and cost-efficient serving design
• Experience supporting external-facing AI APIs at scale

Visa Status: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. Our client cannot sponsor new H-1B visa petitions for this position.

How We Work with You

Candidates apply directly through Get A Job.ai. Our talent team will conduct an initial screening to understand your background and confirm alignment with the role requirements. Once we determine you're a strong match, we will submit your profile to our client for consideration. Please do not attempt to contact the client directly, as all communication and coordination will be managed through our recruiting team to ensure a smooth process.

Pay

This is a full-time, direct W2 position. Salary range: $74,000–$98,000 annually, based on experience and qualifications.

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