Machine Learning Engineer Job at Openkyber, Ohio

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  • Openkyber
  • Ohio

Job Description

Title: Lead AI-ML Engineer

Location: Westerville, OH

Key Responsibilities:
  • Collaborate with stakeholders to understand business objectives and define requirements for anomaly detection.
  • Develop, optimize, and maintain computational models for debit transaction anomaly detection using AI/ML techniques.
  • Perform data analysis, generate insights, and identify patterns to support decision-making.
  • Design and implement statistical models, including standard deviation calculations, variance thresholds, and probabilistic models to enhance anomaly detection accuracy.
  • Work with existing models to apply backtracking methodologies and improve anomaly reduction strategies.
  • Leverage machine learning algorithms (e.g., classification, clustering, time-series modeling) to predict, detect, and manage anomalies.
  • Collaborate with engineers and business teams to integrate models into production systems.
  • Conduct performance monitoring, fine-tuning, and validation of ML models to ensure accuracy and reliability.
  • Prepare technical documentation, visualizations, and reports to communicate findings effectively to business and technology stakeholders.
Required Skills & Qualifications:
  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
  • 10+ years of hands-on experience in data science, AI, or ML engineering.
  • Strong proficiency in Python, R, or Scala with experience using data science libraries (e.g., NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow).
  • Solid understanding of Data Science with a heavy focus on statistical modeling and Machine Learning, hypothesis testing, regression analysis, and variance modeling.
  • Experience with anomaly detection techniques - supervised, unsupervised, and hybrid approaches.
  • Experience in Generative AI based implementations.
  • Expertise in working with large datasets using SQL, Spark, or similar data-processing frameworks.
  • Strong problem-solving, analytical thinking, and communication skills.
  • Experience in deploying ML models into production environments, MLOps, preferably on AWS.

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