Senior AI Engineer

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Requirements

Role: Senior AI Engineer ​

Location: Charlotte,NC

Exp: 6-9 Years

Requirements

We are seeking a Senior AI Engineer to join our advanced analytics and data science team, supporting high-impact machine learning initiatives across the organization. This role is ideal for someone passionate about designing, developing, and deploying scalable AI/ML solutions in real-world, production-grade environments.

Key Responsibilities:

• Design, build, and deploy machine learning models to solve business-critical problems in areas such as risk modeling, financial forecasting, and customer analytics.
  

• Collaborate with data engineers, product managers, and business stakeholders to understand requirements and deliver scalable solutions.
  

• Use MLOps practices and tools to deploy, monitor, and maintain ML pipelines in production.
  

• Work with large-scale datasets using SQL, Pandas, or Apache Spark for feature engineering, model training, and evaluation.
  

• Perform rigorous model validation, testing, and documentation to ensure reliability, accuracy, and compliance.
  

• Implement interpretability techniques and explainable AI approaches to drive stakeholder trust and regulatory compliance.
  

• Ensure continuous performance tracking, re-training, and improvement of deployed models.
  

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science , Machine Learning , Data Science , or a closely related field.
  

• 6 to 9 years of experience in AI/ML engineering or data science roles.
  

• Proficiency in Python and experience with ML libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, and XGBoost .
  

• Strong knowledge of SQL and hands-on experience with data processing tools like Pandas or Spark .
  

• Demonstrated experience deploying ML models in cloud environments such as AWS, GCP, or Azure .
  

• Familiarity with MLOps tools like MLflow, Kubeflow, or SageMaker for model versioning and deployment.
  

• Solid understanding of model validation , performance tuning , and monitoring techniques.
  

Preferred Qualifications:

• Previous work experience in financial services or banking , particularly in:
  

  • Credit scoring or underwriting
    

  • Fraud detection
    

  • Risk modeling or regulatory reporting
    

• Experience working with big data technologies like Hadoop, Spark .
  

• Exposure to CI/CD pipelines , Docker , and Kubernetes for containerized model deployment.
  

• Awareness of Responsible AI principles, including fairness , bias detection , and model explainability .
  

Nice to Have:

• Contributions to open-source AI/ML projects or published research.
  

• Experience with time series modeling, NLP, or deep learning techniques.
  

Benefits

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