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Data Engineer

Expert In Recruitment Solutions

  • Malvern, PA
  • 30+ days ago

    Highlights

    You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines, and building scalable AI/ML solutions, including large language models (LLMs). The ideal candidate will possess a robust background in traditional machine learning, deep learning, and significant experience with large datasets and cloud-based AI services.

    Numbers & Facts

    LocationMalvern, PA

    Description

    Data Engineer
    Hybrid Malvern, PA

    Responsibilities
    • We are seeking an experienced Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines, integrating model pipelines, and building scalable AI/ML solutions, including large language models (LLMs). The ideal candidate will possess a robust background in traditional machine learning, deep learning, and significant experience with large datasets and cloud-based AI services.
    • Develop and optimize complex data pipelines, applying machine learning engineering principles to enhance efficiency and scalability.
    • Integrate and optimize data and model pipelines within production environments, diagnosing data inconsistencies and documenting assumptions.
    • Collaborate with data science teams to review model-ready datasets and feature documentation, ensuring completeness and accuracy.
    • Perform data discovery and analysis of raw data sources, applying business context to meet model development needs.
    • Comfort with exploratory data exploration and tracking data lineage during inception or root cause analysis.
    • Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts.
    Qualifications
    • Around 5-8 years of relevant work experience (Machine Learning Engineering).
    • At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).
    • Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.
    • Robust understanding of cloud technologies, including AWS and Azure.
    • Experience with API design and development is a plus.
    • Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
    • Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.

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