Machine Learning Engineer-(Hybrid)

job
  • Shuvel Digital
Job Summary
Location
Vienna ,VA 22184
Job Type
Contract
Visa
Any Valid Visa
Salary
PayRate
Qualification
BCA
Experience
2Years - 10Years
Posted
01 Feb 2025
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Job Description
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.
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.
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