About the role

On-site ML engineering role owning production ML and LLM systems for internal operations, including forecasting, document extraction, retrieval, agents, evaluations, and guardrails.

Requirements

• Shipped ML or LLM features to production and owned them after launch
• Built evaluation harnesses for model quality
• Hands-on experience with LLM APIs, fine-tuning, or retrieval
• Production-quality software engineering
• Ability to choose and defend the simplest effective model
• Forecasting, scheduling, document extraction, agentic frameworks, MCP, or workflow engines are bonuses

What you'll do

• Build ML and LLM systems for forecasting, schedule-risk detection, and vendor-document extraction
• Own models end to end from framing and data through deployment and iteration
• Ship agentic systems with guardrails, authorization, audit, and evaluations
• Partner with data engineering and product teams to integrate predictions into operational tools

Where this was posted

• linkedin.com
  https://linkedin.com/jobs/view/444138526121d ago