Machine Learning Engineer

1 week ago


Rockville, United States ASCENDING Full time
Job DescriptionJob Description

- 100% Remote within the US / Must have background in financial industry. 


Responsibilities

As a Machine Learning Engineer, you will be a crucial part of our tech team, focused on the innovative application of machine learning techniques across various domains. Your key responsibilities will include:

  • Building and enhancing machine learning models through all phases of development, including design, training, validation, and implementation.
  • Unlocking insights by analyzing large scales of complex numerical and textual data and identifying trends.
  • Collaborating with a cross-functional team, including data engineers, data scientists, and data visualization experts, to deliver impactful projects.
  • Researching and evaluating emerging technologies in the field.
  • Developing data science solutions leveraging modern tools and cloud computing infrastructure.
  • Fulfilling additional duties as assigned.
Qualifications

The ideal candidate will possess:

  • A Bachelor’s degree in Computer Science, Mathematics, Physics, Statistics, or a related field.
  • Demonstrated experience with model design, training, validation, and monitoring.
  • An excellent understanding of machine learning, statistical modeling, and algorithms, including their benefits and drawbacks.
  • Advanced proficiency with Python, Jupyter Notebook/Lab, Visual Studio Code, and other languages suitable for large-scale data analysis.
  • Experience with cloud computing infrastructure.
  • Advanced SQL skills.
  • Familiarity with data visualization concepts and tools.
  • The ability to translate complex business problems into technical solutions.
  • Strong capability to work both independently and as part of a team.
  • Exceptional verbal, written, interpersonal, and presentation skills to communicate technical and non-technical information to all levels of management.
Desired Skills

Preferably, candidates will also have:

  • An advanced degree in Computer Science, Mathematics, Physics, Statistics, or a related field.
  • Experience with Natural Language Processing (NLP).
  • Proficiency with deep learning frameworks and infrastructure, such as TensorFlow or PyTorch.
  • An eagerness to learn and apply techniques in Large Language Models (LLMs) and Generative AI.
  • Expertise in AI model optimization on GPU architecture, including knowledge of C++ and CUDA.
  • The willingness to research, develop, implement, and fine-tune LLMs tailored to specific domain knowledge and use cases.
  • Knowledge of Machine Learning Ops (MLOps) and CI/CD tools for automating the build, test, and deployment of models in production environments.

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