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AI/ML - Data Engineer (Python, Gen AI, ML Modeling)

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Job Title: AI/ML - Data Engineer (Python, Gen AI, ML Modeling) Location: New York, NY (Hybrid - 3 Days Onsite) Job Description: We are seeking an experienced AI/ML Data Engineer to analyze large datasets, build machine learning models, and develop data-driven solutions that support business decision-making. The ideal candidate will have strong experience in Python, machine learning modeling, and big data technologies, along with the ability to collaborate with cross-functional teams to deliver scalable data solutions. Key Responsibilities:

  • Analyze large and complex datasets to derive actionable insights and support business strategies.
  • Develop, train, and implement advanced machine learning models and algorithms.
  • Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions.
  • Communicate analytical findings, insights, and recommendations to stakeholders and executive leadership.
  • Stay updated with the latest advancements and technologies in data science, machine learning, and AI.

Basic Qualifications:

  • Bachelor's degree in Computer Science, Statistics, Applied Mathematics, or a related field.
  • Minimum of 8 years of experience in a data science or data engineering role.
  • Strong proficiency in Python and libraries such as Pandas, NumPy, and Scikit-Learn.
  • Experience working with PySpark for large-scale data processing.
  • Strong understanding of machine learning techniques and algorithms.
  • Proficiency in programming languages such as Python or R.

Preferred Qualifications:

  • Experience with modern ML frameworks such as PyTorch or TensorFlow.
  • Experience with big data technologies such as PySpark.
  • Experience training and deploying ML models in cloud environments such as Azure, AWS, or GCP.
  • Proven experience deploying and optimizing machine learning models in production environments.
  • Strong communication and data visualization skills to present insights to non-technical stakeholders.

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