Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).
Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.
Join us to deploy and implement cutting-edge AI/ML models addressing complex challenges in life science R&D areas including target choice, patient identification, molecule design and clinical trial effectiveness. Collaborate with data scientists and leverage cloud infrastructure to build scalable training pipelines, ensuring rapid iterations and operational excellence. Develop robust backend systems and evaluation frameworks while engaging in technology assessments and co-development with strategic partners to support GenAI products across R&D functions.
Job Description
● Deploy and implement advanced AI/ML models to tackle complex problems in target choice, patient identification, molecule design/chemistry, manufacturing and controls (CMC), and clinical trial effectiveness.
● Design and implement distributed training pipelines for LLMs using tools such as DeepSpeed, ensuring scalability and efficiency.
● Collaborate with Data Scientists in LLM customization: pre-training, fine-tuning, reinforcement learning with human feedback (RLHF), and applying parameter efficient fine-tuning (PEFT) techniques.
● Define and implement repeatable AI/ML pipelines to ensure rapid iterations of data science experiments while leveraging the cloud infrastructure to implement industry best practice in MLOps.
● Model operationalization and monitoring on Azure and GCP infrastructures with close collaboration with the DevSecOps team.
● Build scalable, reusable backend systems including the state-of-the-art agentic frameworks to support GenAI products across R&D functions. Develop robust logging, telemetry, and evaluation harnesses to ensure reliable model performance.
● Technology assessment of external product solutions and co-development with strategic partners
● Create and maintain pipelines for producing training/testing/validation data sets
● Build and maintain model evaluation framework
● Build strong relationships with key stakeholders across GSK, effectively communicating the value proposition of AI/ML and fostering a culture of data-driven decision-making.
● Develop and manage budgets, resource allocation, and timelines for responsible AI/ML projects
● Recruit and develop AI/ML talents, set direction/objectives, and manage overall on-time high-quality delivery.
● Continuously benchmark GSK AI/ML capabilities, stay ahead of industry trend, identify opportunities for optimization and innovation to drive great impact and ROI.
Basic Qualifications
● BS degree in computer science, engineering, or equivalent quantitative science fields (e.g., bioinformatics, applied math)
● 10+ years of engineering experience in high-velocity, high-growth companies.
● Strong track record of working with LLM technologies, including GenAI embedding techniques, modern model architecture, retrieval-augmented generation (RAG), fine tuning/pre-training AI models, and evaluation benchmarks
● Proficiency in Python, TensorFlow/PyTorch, and scalable ML architectures.
● Proficiency in Agentic framework, i.e., AutoGen and LangGraph
● Proficiency in Azure and GCP cloud services
● Expertise in full stack software development, and familiarity with software engineering principles around testing, code reviews and deployment.
● Strong analytical and problem-solving skills, with a passion for shaping AI-driven workflow.
● Strong written and verbal communication skills
● 5+ years of people leader experience to scale one or more technical capability areas
Preferred Qualifications
● MA degree in computer science or engineering
● 10-15 years of combined full stack, data engineering, Azure/GCP cloud services, and AI engineering experience
● Experience with graph databases in the context of GraphRAG
● Experience with data lake-house architecture, data catalog, master data management applications
● Experience in establishing AI/ML and agent best practices, standards, and ethics
● Experience in AI/ML applications in life science domain areas: pre-clinical research, clinical trial design and operation, precision medicine, regulatory science, and CMC.
● Experience in reducing the cost of running a service / capability while maintaining or improving performance efficiencies
Please visit GSK US Benefits Summary to learn more about the comprehensive benefits program GSK offers US employees.
Why GSK?
Uniting science, technology and talent to get ahead of disease together.
GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).
Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.
If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).
GSK is an Equal Opportunity Employer and, in the US, we adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class.
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GSK does not accept referrals from employment businesses and/or employment agencies in respect of the vacancies posted on this site. All employment businesses/agencies are required to contact GSK's commercial and general procurement/human resources department to obtain prior written authorization before referring any candidates to GSK. The obtaining of prior written authorization is a condition precedent to any agreement (verbal or written) between the employment business/ agency and GSK. In the absence of such written authorization being obtained any actions undertaken by the employment business/agency shall be deemed to have been performed without the consent or contractual agreement of GSK. GSK shall therefore not be liable for any fees arising from such actions or any fees arising from any referrals by employment businesses/agencies in respect of the vacancies posted on this site.
Please note that if you are a US Licensed Healthcare Professional or Healthcare Professional as defined by the laws of the state issuing your license, GSK may be required to capture and report expenses GSK incurs, on your behalf, in the event you are afforded an interview for employment. This capture of applicable transfers of value is necessary to ensure GSK’s compliance to all federal and state US Transparency requirements. For more information, please visit the Centers for Medicare and Medicaid Services (CMS) website at https://openpaymentsdata.cms.gov/
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Join GSK as a Senior Director of AI/ML Engineering in Philadelphia, Pennsylvania, and become a pivotal part of our mission to unite science, technology, and talent to advance healthcare solutions. At GSK, we are not just a biopharma company; we are a dedicated team striving to transform lives and get ahead of diseases through cutting-edge innovations. In this dynamic role, you will lead the deployment and implementation of advanced AI and ML models that solve complex challenges in life science R&D. You'll partner with talented data scientists to customize language models and build scalable training pipelines, ensuring rapid iterations in our work. You will have the opportunity to shape the future of patient identification, molecule design, and clinical trial effectiveness, directly impacting healthcare outcomes. Collaboration will be key, as you develop strong relationships across GSK, fostering a culture of data-driven decision-making. Your expertise in Python, TensorFlow, and cloud services like Azure and GCP will help design robust backend systems that support our GenAI products. This is more than just a job; it’s a chance to contribute to a purpose-driven organization where your ideas can have a monumental impact. If you’re passionate about shaping AI-driven workflows and are excited about leading a stellar team to new heights, we’d love for you to join us in this important journey together.
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