AI/ML Engineer (Embedded)

    • Stevenage, United Kingdom

Site Name: UK - Hertfordshire - Stevenage, UK - London - Brentford, USA - Massachusetts - Cambridge, USA - Pennsylvania - Philadelphia, USA - California - San Francisco
Posted Date: Jul 13 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 a highly skilled AI/ML Engineer to help us make this vision a reality as part of our AI/ML Embedded Engineering function. AI/ML Engineers in this role embed directly with our project teams on exciting, cutting-edge AI/ML work in the Pharma R&D space. They are expected to contribute to the team's output by training models, building data pipelines, and standing up services;but,they should be the strongest members of the team in software engineering, high-performance computing, and generally ensuring that our algorithms can train and operate at scale. This is a unique opportunity to sit in theincreasingly-vitalintersection between software engineering and AI/ML, learning from experts in each. Competitive candidates will have a track record of writing quality, well-documented and well-tested code in the AI/ML space. They should be comfortable in Python, and able to implement a neural network training process inPyTorchor TensorFlow. They should feel comfortable with TensorFlow throwing underlying C++ errors, and have ideas on how to ferret out the source of a bottleneck in a training process.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) or equivalent demonstrated work experience. 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.

Why You? 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.
  • Application and understanding of best practices in Machine Learning, software engineering, and production deployment of ML services
  • Highly accomplished in software engineering with intermediate to advanced skills in python and strong experience inPyTorch,Tensorflow, or other deep learning frameworks
  • Breadth across the ML stack, and experience dealing with computationally complex problems

Preferred Qualifications:
If you have the following characteristics, it would be a plus:
  • Candidates with graduate studies in CS and biological sciences or equivalent work history will be highly competitive.
  • Understanding of modern ML Architectures, Platforms, and backend systems
  • Mentality of commit early and often, metrics before models, and shipping high quality production code

Why GSK?

Our values and expectationsare at the heart of everything we do and form an important part of our culture.

These include Patient focus, Transparency, Respect, Integrity along with Courage, Accountability, Development, and Teamwork. As GSK focuses on our values and expectations and a culture of innovation, performance, and trust, the successful candidate will demonstrate the following capabilities:

  • Agile and distributed decision-making - using evidence and applying judgement to balance pace,rigourand risk
  • Managing individual and team performance.
  • Committed to delivering high quality results, overcoming challenges, focusing on what matters, execution.
  • Implementing change initiatives and leading change.
  • Sustaining energy and well-being, building resilience in teams.
  • Continuously looking for opportunities to learn, build skills and share learning both internally and externally.
  • Developing people and building a talent pipeline.
  • Translating strategy into action - a compelling narrative, motivating others, setting objectives and delegation.
  • Building strong relationships and collaboration, managing trusted stakeholder relationships internally and externally.
  • Budgeting and forecasting, commercial and financial acumen.


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