SuperDial

Machine Learning Engineer

• Build, maintain, and improve supervised fine-tuning pipelines for open-source LLMs.
• Fine-tune models for healthcare administrative workflows involving multi-turn conversations, tool use, structured outputs, and task execution.
• Develop and refine training datasets from expert examples, workflow traces, synthetic data, user interactions, and model failure cases.
• Create evaluation frameworks to measure task completion, instruction following, factual grounding, tool-use accuracy, and regression quality.
• Analyze model failures and translate findings into improvements across data, training, prompting, retrieval, tooling, and product behavior.
• Collaborate with healthcare and RCM experts to learn workflows and convert domain knowledge into model behavior.
• Support production deployment, monitoring, and continuous model improvement.

Staff Machine Learning Engineer