Machine Learning Engineer, Agent Platforms

What you'll do

• Design and build production LLM and agent systems for enterprise clients.
• Build the evaluation and governance layers that let a client's risk committee approve a production deployment.
• Partner with client data teams to connect agent platforms to existing data infrastructure.
• Own model performance monitoring and drift detection for deployed systems.
• Document architecture decisions clearly enough for a client team to maintain the system after handoff.

What you'll bring

• 5+ years of experience building and deploying machine learning systems in production.
• Hands-on experience with LLM application development, including retrieval, evaluation, and agent orchestration frameworks.
• Strong Python skills and experience with at least one major ML platform, such as SageMaker, Azure ML, or Vertex AI.
• Experience explaining model behavior and limitations to non-technical stakeholders.
• Comfortable working across multiple concurrent client engagements.

Nice to have

• Experience with MLOps tooling such as MLflow or Kubeflow.
• Published research or open source contributions in applied machine learning.
• Experience in a client-facing consulting role.