ML Engineer II- Gen AI

3+ years of professional experience working in Machine Learning and Data Science. Bachelor’s or Master’s Degree in Computer Science, or equivalent level of demonstrable professional competency. Knowledge of ML Ops good practices for model development, deployment and monitoring. Expert in Python programming language. A strong understanding of AWS cloud technologies such as S3, EC2, RDS, etc. Experience developing model pipelines using AWS Sagemaker. Experience using statistical learning algorithms such as GLM, XGBoost, and Random Forest to solve real world business problems. Deep understanding of neural network and transformer algorithms for large language and chat models. Familiarity with the setup and use of various open source LLM foundation models. Prompt engineering and fine tuning concepts for LLM performance. Creating and using vectorized databases for data storage and retrieval. Familiarity with various LLM architecture patterns such as RAG and FLARE. Understanding of LLM performance evaluation and monitoring using NLP and LLM-assisted metrics. Preferred Skills Data engineering experience with SQL, Spark or AWS Glue. Experience using Docker or Kubernetes to deploy containerized applications. Creating API services for backend application functionality. Experience using TeamCity and Terraform for infrastructure setup and CI/CD. Insurance industry or related experience such as banking and finance.

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