Associate Director, Artificial Intelligence and Machine Learning

Alnylam Pharmaceuticals - Cambridge, MA

Full-time - Mid Level

Cambridge, MA

Chemical Manufacturing

About the position

The Associate Director, Artificial Intelligence and Machine Learning at Alnylam Pharmaceuticals will lead the newly established AI Center of Excellence, focusing on the development and execution of advanced generative AI and Machine Learning solutions. This role emphasizes the integration of AI capabilities into existing systems and workflows, ensuring responsible AI practices while driving innovation and business results.

Responsibilities

• Lead the design, development, and delivery of AI and Machine Learning solutions focused on NLP, ML, and Robotic Process Automation.
• Execute prioritized AI portfolio projects, reinforcing technology innovation and responsible AI practices throughout the project lifecycle.
• Proactively identify opportunities where AI and ML can deliver business results and integrate AI capabilities with existing systems.
• Stay updated on the latest developments in AI and ML and incorporate advancements into the organization.
• Conduct deep data and model analysis on Large Language Models to derive optimal solutions for business insights.
• Collaborate with leaders and stakeholders to drive AI initiatives aligned with strategic objectives.
• Promote a culture of continuous learning and knowledge sharing in AI and Machine Learning technologies.
• Liaise with vendors to select products or services that meet organizational goals.
• Select and implement appropriate tools, software, applications, and systems to support AI & ML goals.

Requirements

• Bachelor's degree in computer science, Engineering, Data Science, Statistics, or a related field; Master's degree or PhD preferred.
• Minimum of 5 years of hands-on experience in Python programming.
• Minimum of 1 year of expertise in designing and implementing AI and ML algorithms using Python.
• Hands-on experience with open-source LLM/CV models and platforms such as Hugging Face, RAG, LangChain, and AWS Bedrock.
• Experience in the complete ML development lifecycle, utilizing frameworks like Pytorch, Tensorflow, and Lightning.
• Solid understanding of deep learning architectures, including CNN and RNN.
• Experience in deploying ML models using AWS services, notably SageMaker, EC2, and Lambda.
• Demonstrable expertise in vector databases, with practical experience in tools like Pinecone and AWS Kendra.
• Proven project management experience and ability to take ownership of challenges from start to finish.
• Good knowledge of applicable data privacy and regulatory practices in biopharma.

Nice-to-haves

• Preferred experience in the pharmaceutical or healthcare industry.