AI/ML Engineer (Production)

3+ months agoSan Francisco, CA

Site Name: USA - Massachusetts - Cambridge, USA - Pennsylvania - Philadelphia, USA - California - San Francisco
Posted Date: Aug 30 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 are seeking to grow our team with brilliant and diverse contributors with technical ability. We are looking for machine learning and infrastructure experts that want to be part of a team that discovers new medicines. The role of an AI/ML Production Engineer is an exciting opportunity 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. Our mission on the AI/ML Platform Engineering team is to provide deep computing expertise, automated workflows, production-grade infrastructure, and helpful tooling to enable the AI/ML team and our partners to solve cutting-edge research problems in the pharma space and translate their solutions into a direct impact on the business and on patients. The Production Engineer function embeds directly with AI/ML project teams doing cutting-edge work, serving as the voice of expertise in software engineering, scientific computing at scale, and expert problem-solving.

This role will provide YOU the opportunity to lead key activities to progress YOUR career. As a AI/ML Production Engineer, we'd like you to be able to:

  • Embed with AI/ML and data science project teams to provide deep expertise in software engineering, parallel computing, and big data tools
  • Stand up useful tools such as AutoML (e.g. Uber's Ludwig, autosklearn, ...) and integrate them with metadata-driven training and production deployment workflows
  • Help to guide the AI/ML Platform Engineering team's efforts based on first-hand experience on projects using our tools
  • Work with partners in data platform, scientific computing, and similar teams to ensure the AI/ML org has the data, computing resources, and workflows/abstractions needed to do our best work.
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.
  • Experience with and understanding of best practices in Machine Learning, software engineering, and production deployment of ML services
  • Experience in software engineering with intermediate to advanced skills in Python and experience in PyTorch, Tensorflow, or other deep learning frameworks
  • Experience across the ML stack, and 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 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:
  • Agile and distributed decision-making - using evidence and applying judgement to balance pace, rigour and 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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