Lead Machine Learning Engineer, AI Innovations

Overview: Lead Machine Learning Engineer, AI Innovations at Incyte

Incyte, a biopharmaceutical company, is dedicated to the discovery, development, and commercialization of novel medicines for serious unmet medical needs in oncology, inflammation, and autoimmunity. We are committed to excellence in research and development to improve patient lives, make a difference in healthcare, and build sustainable value. Our mission is to discover and develop first-in-class and best-in-class medicines, advancing a diverse portfolio of large and small molecules.

We are seeking a highly skilled Lead Machine Learning Engineer to join our dynamic team within the AI Innovations Institute. This pivotal role focuses on the development, deployment, and maintenance of advanced AI agents that leverage Large Language Models (LLMs) to support various critical functions across Incyte. The ideal candidate will possess a robust background in machine learning, extensive experience with cloud-based infrastructures, and a strong passion for applying cutting-edge AI solutions to real-world challenges within the pharmaceutical industry.

Key Responsibilities

• Design, develop, and deploy sophisticated AI agents utilizing LLMs to support diverse functions, including critical research, clinical operations, and commercial activities.
• Collaborate effectively with cross-functional teams to proactively identify opportunities for AI integration and to tailor innovative solutions to specific departmental needs.
• Implement scalable machine learning models, ensuring seamless integration with existing systems and established workflows.
• Utilize a comprehensive suite of AWS services to build and maintain robust, secure, and highly efficient AI infrastructures.
• Continuously monitor and rigorously evaluate the performance of deployed AI agents, making iterative improvements based on valuable feedback and in-depth data analysis.
• Stay abreast of the latest advancements and emerging trends in AI and machine learning to continuously enhance the institute's capabilities and competitive edge.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a closely related quantitative field.
• Proven extensive experience in developing and deploying machine learning models, with a particular emphasis on those involving Large Language Models (LLMs).
• Strong proficiency in Python programming and familiarity with leading machine learning frameworks such as TensorFlow or PyTorch.
• Hands-on experience with key AWS cloud services, including but not limited to EC2, S3, Lambda, and SageMaker.
• A deep understanding of AI agent architectures and their practical applications in automating complex tasks.
• Exceptional problem-solving skills and the demonstrated ability to work collaboratively and effectively within a multidisciplinary environment.

Preferred Qualifications

• AWS certifications, such as Solutions Architect Associate or Professional, are highly desirable.
• Previous experience in the pharmaceutical or healthcare industry, coupled with an understanding of the unique challenges and opportunities prevalent in these fields.
• Familiarity with MLOps practices and relevant tools for continuous integration and deployment of machine learning models.
• Comprehensive knowledge of data privacy regulations and best practices for securely handling sensitive information.

Key skills/competency

• Machine Learning
• Large Language Models (LLMs)
• Python
• AWS Cloud Services
• TensorFlow
• PyTorch
• AI Agent Development
• MLOps
• Data Privacy
• Biopharmaceutical Industry