Machine Learning Engineer

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Responsibilities

The Machine Learning Engineer will investigate, implement, and develop novel algorithms using machine learning techniques. They will analyze data from various sources, both internal and external, create pipelines and algorithms to simulate and augment both real and synthetic data, and develop custom ML algorithms to address detection challenges. The role involves using a variety of ML techniques, including deep neural networks.

The engineer will deepen their understanding of the scientific principles behind the data by collaborating with relevant subject matter experts such as bioinformaticians and detector physicists when necessary. They will be responsible for writing high-quality software, taking ownership of specific areas of the codebase, and collaborating closely with other developers and scientists.

Qualifications & Skills:

• A good understanding of modern machine learning techniques
• A good foundation of coding practices, preferably in Python
• A reasonable proficiency with Python
• Proficiency with PyTorch or Tensor Flow
• A critical mindset and understanding of scientific principles
• Ability to work in a team of scientists and exchange views and ideas based on evidence
• A quality degree in a scientific or software discipline
• Able to work with, process and manage large amounts of data
• High proficiency with Python
• Knowledge of SQL
• Proficiency with Julia
• Familiarity with Linux
• Experience of cloud deployment of software, e.g. AWS
• Knowledge of a Python API package such as FastAPI
• Experience developing software as part of a team
• Familiarity with version control systems, especially git
• High proficiency with PyTorch and Tensor Flow
• Ability to confidently produce and deliver presentations on their work, within a team and to a wider audience
• Ability to create and maintain relationships with external collaborators

• Mid-Senior level

• Full-time

• Information Technology
• Software Development