ViiV (GSK) Machine Learning Engineer

Role Summary

We are ViiV Healthcare. Here until HIV and AIDS are not. 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.

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.

Qualifications

• Required: Bachelor's Degree in Computer Science, Applied Mathematics, Engineering, or equivalent practical experience.
• Required: 5+ years of experience building and deploying machine learning and AI models in production.
• Required: Experience in Python, SQL and experience with at least one deep learning framework (PyTorch, TensorFlow, or similar).
• Required: Experience in one or more of the following fields of applied ML ‚Äì Recommendations, Personalization, Large Language Models (LLMs), LLM Evals
• Required: Experience with cloud technology stack (Azure, GCP or AWS) and ML development environments (DataBricks, MLFlow)
• Required: Software engineering practices: testing, code reviews, CI/CD, and containerization.
• Preferred: Advanced degree (Masters or PhD) in Machine Learning, Computer Science, or related field.
• Preferred: Experience with patient data, payer data, clinical data and familiarity with relevant data formats.
• Preferred: Experience optimizing models for scale, latency, and cost
• Preferred: Experience in managing ML and AI in production including data drift tracking, model governance, validation, and responsible AI practices.
• Preferred: Track record of shipping ML-powered products or services in industry.
• Preferred: Contributions to open-source projects or peer-reviewed publications.
• Preferred: Clear communication skills and experience working with cross-functional teams.

Skills

• Machine learning engineering
• Production ML systems
• Python, SQL
• Deep learning frameworks (PyTorch, TensorFlow)
• Cloud platforms (Azure, GCP, AWS)
• Data pipelines, model versioning, MLOps
• Experimentation and metrics
• CI/CD and containerization

Education

• Bachelor's Degree required; advanced degree preferred as listed in Qualifications

Additional Requirements

• Hybrid role based out of Durham, NC