Machine Learning Engineer

About Verbal

Verbal is dedicated to ensuring every patient receives promised care by auditing patient interactions, both human and AI-driven, in real time to verify compliance with clinical and customer-specific standards.

Role Overview

As a Machine Learning Engineer, you will be responsible for developing, deploying, and optimizing models that score live patient interactions, focusing on migrating critical workloads to self-hosted and fine-tuned models.

Key Responsibilities

• Develop models that evaluate live patient interactions against clinical protocols.
• Deploy and manage open-weight models on cloud GPUs optimized for latency, throughput, and cost-efficiency.
• Fine-tune models using domain-specific data and validate their performance against managed AI services.
• Create rigorous evaluation pipelines for validating model updates and monitor models in production.

Candidate Profile

• Possess 2 to 5 years of experience delivering machine learning systems in production environments with proficiency in Python.
• Hands-on expertise in GPU model serving and fine-tuning language models.
• Strong ability to differentiate meaningful improvements from statistical noise through rigorous evaluation.
• Experience managing sensitive healthcare data responsibly coupled with effective written communication skills.
• Holds a Bachelor's or Master's degree from a premier engineering institute.
• Experience contributing to software product development, preferably in startups.

Preferred Qualifications

• Experience transitioning workloads from managed AI APIs to self-hosted models.
• Familiarity with speech or conversational data processing.
• Background in healthcare industry applications.