Oct 20 2020
At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer side effects.
It is an ambitious vision that will require the development of products and solutions at the cutting edge of Machine Learning and AI.
If that excites you, we'd love to chat.
We're looking for an AI / ML Engineer to help us make this vision a reality. Competitive candidates will have a track record in developing SOTA deep learning models for solving challenging real-world scientific problems.
They should be an outstanding scientist with in-depth knowledge in modern machine learning. They can execute and deliver AI / ML driven solution from sourcing training data, design and implementing SOTA machine learning models, testing, benchmark and product driven research for model performance improvement, to shipping stable, tested, performant code and services in an agile environment.
Educational or professional background in the biological sciences is a plus but is not necessary.
The AI / ML team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work.
Our leaders will be committed to your career and development from day one.
Basic Qualifications :
We are looking for professionals with these required skills to achieve our goals :
Graduate studies in Computer Science or Applied Math, undergraduate studies in Computer Science and relevant graduate studies in the life sciences with a focus on AI / ML techniques, or undergraduate studies in Computer Science and equivalent work history.
Candidates with graduate studies in CS and biological sciences or equivalent work history will be highly competitive.
Experiences in developing deep learning models
Demonstrate expertise and depth in at least one area (scientist, machine learning engineer, software engineer) and breadth across your expertise
Proficiency with standard deep learning algorithms and model architectures
Familiarity with current deep learning literature and math of machine learning
Knowledge in machine learning best practices, scalable training and deployment, model introspection and evaluation
Advanced level in PyTorch, Tensorflow, or other deep learning frameworks
Experienced / accomplished in software engineering with advanced skills in python and / or C++
Experience with DevOp stacks : version control, CI / CD, containerization, etc.
Preferred Qualifications :
If you have the following characteristics, it would be a plus :
Experience in design, development and deployment of commercial AI / ML software.
Track record of contributing to open source projects
Mentality of commit early and often, metrics before models, and shipping high quality production code
Knowledge in disease biology, molecular biology and biochemistry
Experience with biological data (e.g., genomics, transcriptomics, epigenomics, proteomics, etc.), clinical data (e.g., electronic health records, clinical images)