Transforming Healthcare through AI and Machine Learning Expertise

3 weeks ago


San Francisco, California, United States GlaxoSmithKline Full time
Unlock the Power of AI and Machine Learning at GlaxoSmithKline

We are seeking a highly skilled software engineer to join our team in developing a first-in-class platform for high-performance computing, model training, and deployment. As part of our ambitious vision, you will play a critical role in reducing AI/ML cycle times and raising the quality bar on shipped services by simplifying platform integration and accelerating R&D end-to-end.

About the Role
  • Design, build, and ship high-quality, well-documented, and well-tested software in the AI/ML industry.
  • Collaborate with cross-functional teams to develop and deploy cutting-edge AI/ML solutions.
  • Work with modern cloud-native computing environments, such as Docker/Kubernetes/Helm, distributed systems, and high-performance computing frameworks.
Requirements
  • Bachelor's or graduate degree in Computer Science, preferably focused on software engineering, high-performance computing, or machine learning.
  • 2+ years of industry experience in software design or architecture.
  • Experience in Python and deploying APIs/backend services.
  • Experience developing services and infrastructure on GCP.
Preferred Qualifications
  • Software development experience on event-based orchestration platforms, distributed data systems, or similar systems.
  • Collaboration and customer-first mindset; ability to work effectively with Platform and Infra teams, and machine learning product teams.
  • Experience in DevOps and machine learning orchestration (using TensorFlow, PyTorch, or similar).

Salary: $150,000 - $200,000 per annum, depending on location, skills, experience, and education level.

This position offers an annual bonus, eligibility to participate in our share-based long-term incentive program, and comprehensive benefits, including health care and retirement benefits, paid holidays, vacation, and parental leave.



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