Lyric, formerly ClaimsXten, is a leading healthcare technology company, committed to simplifying the business of care. Over 30 years of experience, dedicated teams, and top technology help deliver more than $14 billion of annual savings to our many loyal and valued customers—including 9 of the top 10 payers across the country. Lyric’s solutions leverage the power of machine learning, AI, and predictive analytics to empower health plan payers with pathways to increased accuracy and efficiency, while maximizing value and savings. Lyric’s strong relationships as a trusted ally to customers resulted in recognition from KLAS as “true partner” and “excellent value for investment,” with a top score for overall customer satisfaction and A+ likelihood to recommend in their October 2023 Payment Integrity and Accuracy Report. Discover more at Lyric.ai.The AI Engineer is an ML engineer who is responsible for building and optimizing machine learning models, retrieval-augmented generation (RAG) systems, and verifiable ML systems that transform how we search and analyze complex medical and insurance data. This role requires a deep understanding of machine learning, LLM technologies, data science, and software engineering. This is an ML-engineering role and

not a data science role

, which means you should be comfortable building production-ready systems. This is

not a research

role.This is a Hybrid role in the HYD office, 3 days a week.

Job Responsibilities

Data engineering: Design and optimize systems capable of processing large volumes of data in both batch and real-time.
Design, implement, and optimize retrieval-augmented generation (RAG) systems that leverage the latest LLM technologies to deliver highly relevant search results at scale.
Develop and refine embedding models, vector databases, and retrieval mechanisms that maximize search relevance while minimizing latency and operational costs.
Create robust evaluation frameworks to measure quality, continuously improve our LLM-based solution based on user feedback and performance metrics.
Build and optimize machine learning models and verifiable ML systems that transform how we search and analyze complex medical and insurance data.
Build and optimize production-ready systems that are scalable and can handle large amounts of data.
Build and optimize agentic systems that can reason and make decisions.
Develop machine learning models in healthcare and insurance settings with the highest standards for safety and quality.
Stay on top of AI and ML security and governance requirements.

Basic Requirements

BS in Computer Science (concentration on machine learning/AI), Engineering, Statistics, or a related field
At least three (3) years of industry experience and specifically with some of the recent Gen AI technologies.
Experience with containerization, Kubernetes, and cloud-native ML technologies such as Kubeflow.
Experience with CI/CD pipelines and automated testing.
High level of proficiency with Python and several ML frameworks.

Preferred Requirements

Experience with medical coding and clinical policy analysis. Exposure to USA healthcare insurance will be an advantage.
Strong understanding of clinical coding standards (e.g., ICD-10, CPT, HCPCS) is an advantage.

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