> Markdown version of [/jobs/ext/3797032-ai-ml-engineer-job-in-charlotte](https://www.wearedevelopers.com/jobs/ext/3797032-ai-ml-engineer-job-in-charlotte). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI ML Engineer job in Charlotte - **Company:** Tech Brains Solutions Inc - **Location:** Charlotte, NC, United States - **Contract:** Permanent contract - **Skills:** Geographic Information Systems, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Business Intelligence Development, Big Data, Cluster Analysis, Continuous Integration, Information Engineering, Data Integrity, Extract Transform Load (ETL), Data Mapping, Data Visualization, Apache Hadoop, Machine Learning, Monte Carlo Methods, Natural Language Processing, NumPy, SAS (Software), Data Processing, Feature Engineering, Apache Spark, Git, Pandas, Matplotlib, Machine Learning Operations, Artificial Intelligence Markup Language (AIML), Data Pipelines, Programming Languages - **Published:** October 17, 2026 - **Apply:** https://jobs.diversity.com/career/2531630/ai-ml-engineer-north-carolina-nc-charlotte ## About the Role * We are seeking a highly analytical and detailoriented Data Scientist to join our team in the reinsurance domain The ideal candidate will leverage data to drive insights into risk modeling pricing strategies claims analysis and portfolio optimization This role requires strong technical expertise business acumen and the ability to communicate complex findings clearly Technical Skills Primary * Programming Languages Python Pandas NumPy Scikitlearn SQL * Statistical Modeling Machine Learning Regression Classification Clustering Time Series Forecasting * Data Visualization Power BI Tableau Matplotlib Seaborn * Big Data Technologies Spark Hadoop basic understanding * Cloud Platforms Azure or AWS especially for data pipelines and model deployment * Data Engineering ETL processes data wrangling and feature engineering * InsuranceReinsurance Domain Knowledge Exposure to actuarial models risk assessment and claims analytics Technical Skills Secondary Nice to Have NOT MANDATORY * R or SAS for statistical analysis * Experience with Natural Language Processing NLP * Familiarity with geospatial data and mapping tools * Knowledge of Monte Carlo simulations and stochastic modeling * Experience with Git and CICD pipelines * Exposure to regulatory frameworks Solvency II IFRS 17 Soft Skills * Strong problemsolving and critical thinking abilities * Excellent communication and storytelling skills for nontechnical stakeholders * Collaborative mindset with crossfunctional teams actuarial underwriting IT * Ability to manage multiple projects and prioritize effectively * Curiosity and continuous learning attitude * High attention to detail and data integrity Qualifying Questions Can you describe a project where you applied machine learning to solve a business problem in the insurance or financial domain How do you ensure the quality and reliability of your data before building models Have you worked with actuarial teams or underwriting departments before If yes how did you contribute to their decisionmaking process Skills Mandatory Skills : AI/GenAI Research Required Skills : AI