Senior Machine Learning Engineer

Qualifications

• Strong candidates will have graduate studies in Computer Science, Applied Mathematics, or the equivalent (or in the life sciences with a focus on machine learning techniques) and 2+ years of industry experience building machine learning powered tools.
• 4+ years of industry experience in machine learning engineering.
• Graduate studies in Computer Science, Applied Mathematics, or Life Sciences with a focus on AI/ML techniques, or undergraduate studies in Computer Science and equivalent work history.
• Experienced in software engineering with advanced skills in python and/or C++.
• Experience in PyTorch, TensorFlow, or other deep learning frameworks.
• Breadth across the ML stack, and depth in at least one discipline.
• Experience with shipping products powered by machine learning.
• Bachelors degree required.
• Academic or industry experience in the biomedical sciences especially genetics, molecular biology, or AI driven drug discovery.
• Understanding and application of best practices in machine learning, software engineering, and/or production deployment of ML services.
• Understanding of modern ML Architectures, Platforms, and backend systems.
• Mentality of commit early and often, metrics before models, and shipping high quality production code.
• Track record of contributing to open source projects.

Responsibilities

• A senior engineer can consistently take a poorly defined problem and formulate clear objectives, then execute on it to build a high performing product or service.
• They are the model for the team in terms of code quality, standards, and best practices, and they act as mentors to junior members of the team.