Description
We are hiring a Senior Machine Learning Platform Engineer to build the infrastructure and engineering workflows that take custom models from development into reliable production use.
You will work with model developers, application engineers, security, and cloud platform teams to turn a model artifact into a secure, scalable inference service.
Responsibilities
- Design and build hosting for custom ML and AI models across AWS and Azure, with particular focus on GPU-backed LLM inference and real-time endpoints
- Package models and their dependencies into reproducible serving workloads
- Provision and configure Kubernetes clusters or other suitable hosting infrastructure
- Develop infrastructure as code and deployment automation
- Build MLOps workflows for model registration, versioning, validation, release, rollback, and retirement
- Partner with application teams to design and prototype agent workflows
- Establish production monitoring for service health, latency, throughput, errors, GPU and other resource use, and model behavior
Requirements
- Hands-on experience hosting LLM inference on GPU infrastructure in a production environment
- Experience building the surrounding model-serving platform for custom models
- Strong software engineering skills, especially Python
- Experience developing infrastructure for ML workloads across AWS and Azure
- Experience provisioning, configuring, and maintaining Kubernetes or another production hosting platform
- Familiarity with LLM agent patterns and production concerns for inference services
Benefits
- Health insurance
- Dental insurance
- Vision insurance
- Long term/short term disability insurance
- Employee assistance program
- Flexible spending account
- Life insurance
- Generous time off policies