ViiV (GSK) Machine Learning Engineer

GSK, Plc.•Durham, NC

77d•Hybrid

About The Position

We are a specialist pharmaceutical company fully dedicated to developing medicines to treat and prevent HIV. Born out of a partnership between GSK and Pfizer in 2009, with Shionogi joining in 2012, our ambition is to end the HIV epidemic. As the pioneers in HIV innovation, we constantly look to push the boundaries of science to develop medicines that can change lives and give people more choice. Beyond our medicines, we are proud of our deep connection with the HIV community and work with partners to advance research and development, address HIV-related stigma, increase access to our medicines and provide funding and support to local community organisations to support their efforts in the HIV response. You will design, build, and deploy machine learning models and AI solutions at scale to accelerate the commercialization of our products. You will collaborate with data scientists, data engineers, product managers and marketing leads to translate real-world problems into clear ML solutions. You will drive measurable impact, grow your skills and help GSK unite science, technology and talent to get ahead of disease together. We are ViiV Healthcare. Here until HIV and AIDS are not. We are seeking candidates who want to make a real impact through applied machine learning. This is a hybrid-role based out of Durham, NC. We welcome applicants from different backgrounds and experiences who bring humility, collaboration, and a commitment to learning.

Requirements

Bachelor's Degree in Computer Science, Applied Mathematics, Engineering, or equivalent practical experience.
5+ years of experience building and deploying machine learning and AI models in production.
Experience in Python, SQL and experience with at least one deep learning framework (PyTorch, TensorFlow, or similar).
Experience in one or more of the follow fields of applied ML - Recommendations, Personalization, Large Language Models (LLMs), LLM Evals
Experience with cloud technology stack (eg Azure, GCP or AWS) and ML development environments (eg DataBricks, MLFlow)
Software engineering practices: testing, code reviews, CI/CD, and containerization.

Nice To Haves

Advanced degree (Masters or PhD) in Machine Learning, Computer Science, or related field.
Experience with patient data, payer data, clinical data and familiarity with relevant data formats.
Experience optimizing models for scale, latency, and cost
Experience in managing ML and AI in production including data drift tracking, model governance, validation, and responsible AI practices.
Track record of shipping ML-powered products or services in industry.
Contributions to open-source projects or peer-reviewed publications.
Clear communication skills and experience working with cross-functional teams.

Responsibilities

Develop and deploy machine learning models for commercial, scientific and operational problems.
Design and implement scalable, production-ready AI and ML solutions
Design and run experiments to measure the impact of models on key business metrics
Collaborate with cross-functional teams to translate domain needs into clear technical requirements.
Build reliable, tested, and maintainable code and services for model training and inference.
Implement scalable data pipelines and ensure model data quality, versioning, and reproducibility.
Monitor model performance in production and iterate to improve reliability and fairness.
Contribute to team standards for ML engineering, testing, and documentation.

Benefits

Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program ViiV offers US employees. All ViiV employees receive the same benefits options and plans as GSK employee.

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