ML Infrastructure Engineer – Scale & Production (Hybrid)

Acceler8 Talent; Cambridge (MA); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Acceler8 Talent in Cambridge, MA is seeking a Member of Technical Staff – ML Engineer to design and build scalable ML training and inference infrastructure in a hybrid setting.

You will develop distributed training systems, GPU scheduling and model-serving services, turning research code into reliable production-ready services and tools that support AI agents and model evaluation. You will troubleshoot complex issues and drive performance improvements.

Qualifications

• 3+ years of experience building and operating production ML infrastructure.
• Strong background in distributed systems, ML platforms, model serving or training infrastructure.
• Experience developing systems and tools used by other engineers or researchers.
• Proven ability to diagnose and resolve complex production issues.
• Familiarity with GPU computing, cloud infrastructure or ML performance optimisation is beneficial.

Responsibilities

• Design and build scalable ML training and inference infrastructure.
• Develop distributed training systems, GPU scheduling and model-serving services.
• Turn research code into reliable, production-ready services and tools.
• Build infrastructure supporting AI agents, model evaluation and experimentation.
• Troubleshoot complex infrastructure failures and improve system performance and reliability.

Skills

Distributed systems

Production ML

Model serving

GPU computing

Cloud infrastructure

Tools

Kubernetes

Docker

GPU scheduling

Job description

Acceler8 Talent in Cambridge, MA is seeking a Member of Technical Staff – ML Engineer to design and build scalable ML training and inference infrastructure in a hybrid setting.

You will develop distributed training systems, GPU scheduling and model-serving services, turning research code into reliable production-ready services and tools that support AI agents and model evaluation. You will troubleshoot complex issues and drive performance improvements.