AI/ML Engineer
GSK
Summary
At GSK we see a world in which advanced applications of Artificial Intelligence will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer side effects. We're looking for an accomplished Machine Learning Engineer to help make this vision a reality.
Job description
In this role, you will imagine and engineer agentic systems and machine learning models to elucidate the molecular mechanisms of disease and accelerate the development of new therapies. You will work with frontier models, foundational genomics models, and multiomics datasets from patients and lab experiments to model aspects of molecular biology and medicinal chemistry that will inform our understanding of disease, drug design and response, and longevity.
Familiarity and experience with genomics and RNA biology is a plus, but not required. This position is open to machine learning engineers with a track record of excellence in other domains who have a desire to learn. Strong candidates will have a track record of shipping high performing AI/ML products, academic excellence, and a passion for solving challenging problems in Artificial Intelligence and Machine Learning.
Basic Qualifications
- Degree in a quantitative or engineering discipline (computer science, bioengineering, physics, mathematics, electrical engineering, etc) or equivalent work experience
- Experience with LLM agents, evals, and agentic workflow design
- Experience in at least one major deep learning framework (Pytorch, Tensorflow)
- Programming expertise in Python
- Experience using Git, SQL, and shell scripting within an artificial intelligence and machine learning engineering stack
- Experience applying machine learning best practices
Preferred Qualifications
- Internship experience as researcher in AIML focused academic lab or AIML engineer or SWE in industry
- Experience working with biomedical datasets (e.g., genomics, transcriptomics, proteomics, electronic health records, clinical images)
- Track record of contributing to open-source projects
- Mentality of commit early and often, metrics before models, and shipping high quality production code
Requirements
- Degree in a quantitative or engineering discipline (computer science, bioengineering, physics, mathematics, electrical engineering, etc) or equivalent work experience
- Experience with LLM agents, evals, and agentic workflow design
- Experience in at least one major deep learning framework (Pytorch, Tensorflow)
- Programming expertise in Python
- Experience using Git, SQL, and shell scripting within an artificial intelligence and machine learning engineering stack
- Experience applying machine learning best practices
Benefits
- Health care
- Insurance benefits
- Retirement benefits
- Paid holidays
- Vacation
- Paid caregiver leave
- Parental leave
- Medical leave
- Annual bonus
- Share based long term incentive program
Company overview
GSK plc (formerly GlaxoSmithKline) is a British multinational pharmaceutical and biotechnology company headquartered in London, England. Founded in 2000 through the merger of Glaxo Wellcome and SmithKline Beecham, GSK has grown to become one of the world's leading healthcare companies with operations in over 150 countries. The company specializes in researching, developing, and manufacturing prescription medicines, vaccines, and consumer healthcare products. GSK's therapeutic areas include respiratory diseases, HIV/AIDS, oncology, immunology, and infectious diseases. The company is particularly renowned for its vaccine portfolio and has been at the forefront of developing treatments for major global health challenges. With approximately 70,000 employees worldwide, GSK maintains a strong commitment to scientific innovation and has a significant presence in key markets including the United States, Europe, and emerging economies. The company's mission is to unite science, technology, and talent to get ahead of disease together, aiming to positively impact the health of 2.5 billion people by the end of the decade.