Machine Learning Engineer-(Hybrid)

Shuvel Digital

Machine Learning Engineer-(Hybrid)

Vienna, VA
Full Time
Paid
  • Responsibilities

    Responsibility :

    • Build and enhance machine learning models through all phases of development including design, training, validation, and implementation etc.
    • Unlock insights by analyzing large scale of complex numerical and textual data and identifying trends.
    • Partner with a cross-functional team of data engineers, data scientists, and data visualization to deliver projects.
    • Research and evaluate emerging technologies.
    • Develop data science solutions based on tools and cloud computing infrastructure.
    • Perform other duties as assigned.

    Qualifications :

    • Bachelor's degree in computer science, mathematics, physics, statistics, or related field.
    • Strong experience with applying expertise in model design, training, validation, and monitoring.
    • Excellent understanding of machine learning, statistical modeling, and algorithms as well as their benefits and drawbacks.
    • Advanced skills with Python, Jupyter Notebook/Jupyter Lab, Visual Studio Code and other languages appropriate for large data analysis.
    • Experience with cloud computing infrastructure.
    • Advanced SQL skills.
    • Experience with data visualization concepts and tools.
    • Ability to convey complex business problems to technical solutions.
    • Ability to work individually, and as part of a team.
    • Advanced verbal, written, interpersonal, and presentation skills to communicate clearly and concisely technical and non-technical information to all levels of management.

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    Desired :

    • Advanced degree in in computer science, mathematics, physics, statistics, or related field.
    • Experience with Natural Language Processing.
    • Experience with deep learning framework and infrastructure like TensorFlow or PyTorch.
    • Experience and/or willing to learn techniques in Large Language Models (LLMs) and Generative AI.
    • A.I. Model Optimization on GPU architecture. Leveraging C++, CUDA.
    • Experience and/or willing to research, develop, implement, and fine-tuning LLMs in terms of specific domains knowledge and user cases.
    • Knowledge of Machine Learning Ops and CI/CD tools for automation of build, test, and deploy models in production environments.