AI Engineer

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Requirements

Role: AI Engineer ​

Location: Charlotte,NC

Exp: 3-6 Years

Requirements

We are looking for a Machine Learning Engineer / Data Scientist with 3–6 years of hands-on experience to join our growing data science team. You will be working on the design, development, and deployment of scalable machine learning models that drive intelligent decision-making across business units. This is an excellent opportunity to contribute to real-world ML products and shape innovative solutions in a data-driven environment.

Key Responsibilities:

• Design and implement machine learning models to address business problems including classification, regression, and clustering.
  

• Collaborate with cross-functional teams including data engineers, software developers, and domain experts to build and integrate ML solutions.
  

• Perform data preprocessing, exploration, and feature engineering using tools like Pandas and NumPy .
  

• Develop and evaluate models using libraries such as Scikit-learn , XGBoost , TensorFlow , or PyTorch .
  

• Work with large-scale datasets to build models that are robust, interpretable, and production-ready.
  

• Monitor model performance and assist in retraining and tuning when necessary.
  

• Document model assumptions, development steps, and performance metrics for internal governance and review.
  

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science , Data Science , AI , Engineering , or related fields.
  

• 3–6 years of experience in machine learning or data science roles.
  

• Proficient in Python , with strong knowledge of ML libraries like Scikit-learn, XGBoost, TensorFlow, or PyTorch .
  

• Comfortable writing and optimizing SQL queries.
  

• Hands-on experience with data wrangling and manipulation using Pandas or similar tools.
  

• Solid understanding of key machine learning concepts: classification, regression, clustering, cross-validation, evaluation metrics, feature selection , and hyperparameter tuning .
  

Preferred Qualifications:

• Exposure to cloud platforms such as AWS , Azure , or Google Cloud Platform (GCP) .
  

• Experience using ML tools like SageMaker , Databricks , or Vertex AI .
  

• Familiarity with MLOps concepts and tools such as MLflow , Airflow , or Kubeflow .
  

• Domain knowledge or prior experience in financial services , especially building models for credit scoring , risk assessment , or fraud detection .
  

• Understanding of regulatory requirements , model documentation standards , and governance protocols in the financial sector.
  

Nice to Have:

• Exposure to model monitoring frameworks and alerting pipelines.
  

• Experience with notebooks (Jupyter, Colab) and version control (Git).
  

• Background in statistics or a quantitative field is a strong plus.
  

Benefits

Visit us at . Alignity Solutions is an Equal Opportunity Employer, M/F/V/D.

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