ML Ops Engineer

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Site Name: USA - California - San Francisco, UK - London - Brentford, USA - Massachusetts - Cambridge, USA - Pennsylvania - Philadelphia Posted Date: Nov 1 2021 At GSK we see a world in which advanced applications of Machine Learning and AI will allow us to develop transformational medicines using the power of genetics, functional genomics, and machine learning. AI will also play a role in how we diagnose and use medicines to enable everyone to do more feel better and live longer. It is an ambitious vision that will require the development of products at the cutting edge of Machine Learning and AI. We're looking for a highly skilled ML Ops Engineer to help us make this vision a reality. Our AI/ML Platform Engineering team is building a first-in-class platform of tools and services covering high-performance computing, ML training services, DevOps, model deployment, and metadata capture; our goal is to decrease AI/ML development/training cycle time and raise the quality bar on AI/ML's shipped services by drastically simplifying the process of AI/ML Engineering. Competitive candidates will have a track record of writing quality, well-documented and well-tested code for services in the AI/ML space. They should be comfortable with modern, cloud-native computing paradigms such as the Docker/Kubernetes/Helm ecosystem, and with high-performance computing on GPUs via frameworks like TensorFlow or PyTorch. They should have a strong sense for the abstractions needed to represent ML processes with little to no tie-in to particular tools in the ever-changing machine learning software ecosystem. Strong candidates will have graduate studies in Computer Science 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 with a focus on software engineering, high-performance computing, or machine learning. Experienced in software engineering with intermediate to advanced skills in python and experience standing up services. Kubernetes experience in this space is a big plus. Preferred Qualifications: If you have the following characteristics, it would be a plus: Candidates with experience explicitly tied to HPC/SWE/DevOps in the AI/ML space will be highly competitive. Understanding and application of best practices for software engineering and high-performance computing in the AI/ML and data spaces Understanding of modern ML platforms and backend systems Mentality of commit early and often, metrics before models/services, and shipping high-quality production code Why GSK? 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 *LI-GSK #GSKAIML2021 #AIMLEngineer If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US). GSK is an Equal Opportunity Employer and, in the US, we adhere to Affirmative Action principles. 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