Machine Learning Engineer
- San Francisco, CA
Site Name: USA - Massachusetts - Cambridge, USA - Pennsylvania - Upper Providence, USA - California - San Francisco
Posted Date: Apr 20 2020
At GlaxoSmithKline we have created a world-leading data and computational environment to enable large scale scientific experiments that exploit GSK's unique access to data. Our focus is on bringing data, analytics & science together into solutions for our scientists to develop medicines for patients.
We are seeking to grow our team with brilliant and diverse contributors with technical ability. We are looking for machine learning experts that want to be part of a team that discovers new medicines. This is an exciting role that will stretch your knowledge and curiosity, offering the opportunity to learn new skills and work within a global community.
This is a hands-on position where you will be empowered to be creative, ambitious and bold, to solve novel R&D problems and have the potential to directly impact the lives of patients living with disease. We have impressive tool-kits and world class data, and we are now looking for talented people to join us.
As a Machine Learning Engineer we'd like you to be able to:
- Influence machine learning strategy for a program/project; explores design options to assess efficiency and impact, develop approaches to improve robustness and rigour
- Be a key contributor to the planning and direction of a project and effectively prioritize goals
- Lead discussions at peer review and uses quantitative skills to positively influence decision making
- Effectively explain technical concepts at all levels in the organization, including senior managers/stakeholders
- Lead, or makes major contributions to, improvements in methodology or initiatives to address capability gaps or increase efficiency
- Represent GSK externally to advance technical capability across the Industry
- Identify opportunities to apply the latest advancements in Machine Learning and Artificial Intelligence to build, test, and validate predictive models
- Create algorithms to extract information from large, multiparametric data sets
- Deploy your algorithms to production to identify actionable insights from large databases
- Compare results from various methodologies and recommend best techniques to stake holders
- Design, develop and implement analytical solutions using a variety of commercial and open source tools (common tools include Python, R, TensorFlow)
- Develop and embed automated processes for predictive model validation, deployment, and implementation
- Connect and collaborate with subject matter experts in biology, chemistry, and medicine.
- Make impactful contributions to internal discussions on emerging machine learning methodologies
It would be fantastic if you have
- A higher degree in Engineering, Statistics, Data Science, Applied Mathematics, Computer Science, Physics, Computational Biology, Computational Chemistry or related quantitative field
- Expert understanding of a programming language such as Python.
- Experience with at least one Deep Learning framework such as TensorFlow, Keras, or PyTorch
- Excellent written and verbal communication skills
- Ability to work autonomously and collaboratively as part of a team to both teach and learn every day
Our values and expectations are 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:
- Operating at pace and agile decision-making - using evidence and applying judgement to balance pace, rigour and risk.
- Committed to delivering high quality results, overcoming challenges, focusing on what matters, execution.
- Continuously looking for opportunities to learn, build skills and share learning.
- Sustaining energy and well-being
- Building strong relationships and collaboration, honest and open conversations.
- Budgeting and cost-consciousness
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