ML Platform Engineer (AI)

Location: 100% remote within the United States; the posting also lists Nashua, NH.

Salary: $100,000–$160,000 annually.

Company

Technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.

What you will do

• Design and operate model-serving platforms for LLM, vision, and recommendation workloads.
• Optimize inference with continuous batching, paged attention, speculative decoding, request multiplexing, caching, and prompt deduplication.
• Build multi-tenant routing, rate limiting, quality-of-service, autoscaling, and capacity-management systems.
• Tune GPU utilization, memory management, and KV-cache strategies for large-model serving.
• Integrate serving platforms with API gateways, identity systems, observability tools, and security controls.
• Develop canary releases, shadow testing, automated rollback, incident response, and reliability improvements.

Requirements

• Must be authorized to work in the United States as a U.S. citizen, Green Card holder, EAD holder, or H-1B transfer candidate; new H-1B sponsorship is unavailable.
• Bachelor’s or Master’s degree in Computer Science or a related field.
• 10+ 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++.
• Experience operating high-throughput, low-latency production services and using LLM or large-model inference frameworks such as vLLM or TensorRT-LLM.
• Experience with GPU architecture, Kubernetes, cloud platforms, autoscaling, observability, performance engineering, capacity planning, communication, and incident response.

Nice to have

• Open-source contributions to model-serving infrastructure.
• Experience with multi-region or globally distributed AI serving.
• Knowledge of model quantization, distillation, compression, FinOps, or external-facing AI APIs at scale.

Culture & Benefits

• Full-time direct W-2 employment.
• 100% remote work within the United States.
• Career growth opportunities within an established organization.
• Equal employment opportunity and anti-harassment commitments.