Senior Director, Machine Learning Developer and Data Scientist

Join our team to develop and validate advanced AI/ML models addressing complex challenges in life science R&D areas such as target choice, patient identification, molecule design and clinical trial effectiveness. Design and implement AI/ML pipelines for rapid experimental iteration, including classical ML models and advanced LLM customization techniques. Collaborate with subject matter experts and AI engineers to develop and deploy models and ensure high-quality, scientifically sound solutions.

Job Description  

• Develop and validate 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 AI/ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid experimental iteration and adhering to industry’s best practices in MLOps.
• Besides classical ML models fine-tuning (i.e., support vector machine and random forest), this team is also responsible for large language model (LLM) customization and fine-tuning using complex techniques (i.e., low-rank adaptation (LoRA) and reinforcement learning (RL) with human feedback).
• Collaborate with AI engineers to deploy AI/ML models in both classical inference pipelines and agentic framework approaches. 
• Collaborate with subject matter experts in pre-clinical research, clinical trial design and operation, precision medicine, regulatory science, and CMC to guarantee scientifically sound and high-quality simulation modeling and analytical solutions.
• 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 or equivalent quantitative science fields (e.g., bioinformatics, applied math, statistics, engineering)  
• 10+ years of data science and machine learning developer experience in high-velocity, high-growth companies. Alternatively, a strong background in relevant ML research in academia will be considered as an equivalent qualification.
• Strong track record of working with LLM technologies, including developing generative and embedding techniques, modern model architectures, retrieval-augmented generation (RAG), fine tuning / pre-training LLM (including parameter efficient fine-tuning), and evaluation benchmarks.
• Proficiency in data wrangling from large databases for feature engineering and model training purposes. 
• Proficiency in Python, TensorFlow/PyTorch, and scalable ML architectures. 
• Proficiency of AI/ML model metrics (e.g., F1 and AI-contents evaluation metrics) including setting up human-in-the-loop AI/ML monitoring. 
• Strong written and verbal communication skills
• Strong coding and software engineering skills, and familiarity with software engineering principles around testing, code reviews and deployment.
• Experience in AI/ML applications in life science domain areas: pre-clinical research, clinical trial design and operation, precision medicine, regulatory science, and CMC.
• 5+ years of people leader experience to scale one or more technical capability areas

Preferred Qualifications 

• MA degree in computer science or equivalent qualitative science fields
• Experience with reinforcement learning (RL) and multi-agent framework
• Experience with graph database in the context of GraphRAG
• Experience with computer vision
• Experience designing and managing AI workloads on cloud platforms and/or high-performance computing environments
• Knowledge of cost optimization strategies for GPU computing in both cloud and on-premises scenarios
• Proficiency with distributed computing frameworks (i.e., Spark, databricks, RAPIDS.ai)
• Experience in establishing AI/ML best practices, standards, and ethics

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