About the Role
At GSK, we are building a future where Artificial Intelligence (AI) and Machine Learning (ML) enable the development of new therapies and personalized drugs, driving better patient outcomes with reduced costs and fewer side effects. This ambitious goal requires cutting-edge AI/ML solutions for transformational medicines. The Applied AI team develops tools, models, and processes that empower scientists to create preventative products, discover illness treatments, and glean insights from vast amounts of multimodal data. Our team fosters a culture of learning and collegiality, with a broad portfolio including work in computer vision, NLP, data science, machine learning, and deep learning. Applied AI/ML Engineers support research scientists with high-dimensional computer vision analysis and up-to-date NLP solutions, such as large language models.
As an AI/ML Engineer II, you will apply established algorithms and novel solutions, packaging them into user-facing AI products for GSK scientists to accelerate drug discovery. This role offers the opportunity to make a high impact, for example, by improving decision cycle times for biopharmaceuticals through data-driven practices and accelerating clinical trial assets via forecasting.
Key Responsibilities
- Develop and deploy machine learning models and algorithms.
- Preprocess large-scale data to ensure data quality and model accuracy.
- Collaborate with cross-functional teams to understand business needs and translate them into technical solutions.
- Evaluate and select product-driven machine learning frameworks, libraries, and tools.
- Review code, present technical solutions, and contribute to our codebase with well-tested, production-ready code.
- Continuously monitor and evaluate the performance of deployed models and make necessary adjustments with data at scale.
- Communicate complex technical concepts to non-technical stakeholders.
- Mentor other engineers and contribute to AIML discourse at GSK and beyond.
Requirements
Basic Qualifications:
- MS degree in Computational Sciences, Engineering, Data Science/ML, Applied Mathematics, Statistics, or a related scientific field with some relevant work experience OR a BS degree with additional years of work experience.
- Experience in machine learning, software engineering, and Python.
- Experience working in a collaborative CI/CD software development environment, including use of git.
- Experience developing computer vision algorithms using PyTorch.
Preferred Qualifications:
- PhD in Computational Sciences, Engineering, Data Science/ML, Applied Mathematics, Statistics, or a related scientific field with relevant work experience.
- Track record of writing software in a collaborative team in industrial environments or open-source projects, applying practices in machine learning, software engineering, and/or production deployment of ML products.
- Applied industry experience with modern ML architectures, statistics, and deep learning.
- Experience shipping scientific products powered by machine learning.
- Knowledge in disease biology, molecular biology, and biochemistry.