Software Engineer I, AI
Indexed description
The AI Engineer is an ML engineer responsible for building and optimizing machine learning models, retrieval-augmented generation (RAG) systems, and verifiable ML systems that transform how Lyric searches and analyzes complex medical and insurance data.
Essential Job Responsibilities & Key Performance Outcomes
- 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.
- 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.
- 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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