Associate Director, AI/ML

Role Summary

Associate Director, AI/ML at the ShinrAI Center for AI/ML, based in Cambridge, MA. Join a team of scientists, engineers, and machine learning experts to advance the application of AI in developing innovative medicine for patients. You will tackle challenging, real-world problems with direct impact and contribute to the center’s governance and long-term strategy.

Responsibilities

• Educate, demonstrate, guide, and enable the application of AI/ML in various pharmaceutical R&D operations and scientific domains
• Partner with data science teams, domain experts, and business units to identify and prioritize opportunities to leverage machine learning to drive decision making and automation across all levels of the R&D organization
• Translate business needs into clearly scoped machine learning projects, and take a hands-on approach to steer solution design and implementation
• Identify, monitor, and validate relevant external AI/ML developments, cultivate relationships with external domain experts and partners, and report and present emerging novel developments within the organization to further innovation and shape long-term strategy and governance
• Proactively build relationships across the company to inform your work and contribute to internal and external collaborations, through involvement in working groups, and the writing of insightful, engaging, and actionable opinion pieces that are easily digestible by internal decision makers and stakeholders
• Be the leading voice for building common capability and approaches and for adopting best practices
• Work in collaboration with our Ethics and Governance teams to ensure our AI/ML applications are developed ethically and provide broad benefits to our patients and business
• Help talented, driven, enthusiastic AI/ML engineers and data scientists across the company grow professionally
• Measure, document, and communicate impacts of the Center‚Äôs efforts

Qualifications

• A track record of partnering cross-functionally with a wide range of stakeholders and cross-functional teams to develop and deploy novel data solutions in production environments
• Demonstrated passion for making complex technology more accessible and the ability to communicate complex technical topics simply and convincingly to a wide range of audiences
• Demonstrated ability in translating big picture business and product ideas into micro use cases and has a strong focus on solving core problems to deliver simple solutions
• Experience recognizing and communicating the implications of emerging technologies
• Excellent communication, prioritization, and interpersonal skills, with a high level of attention to detail
• An advanced degree (M.S., PhD.) in mathematics, applied statistics, computer science, machine learning or similar with 6+ years of experience architecting, building, launching, and maintaining end-to-end ML systems from whiteboard to production at scale across a range of models and platforms; experience in fine-tuning large language models for domain-specific applications; designing transfer learning strategies to enable learning from small datasets; expertise in AI/ML problems and domains with depth in at least two areas (e.g., computer vision, NLP, geometric deep learning, time series, reinforcement learning, multimodal learning); solid understanding of deep learning architectures and traditional ML models; experience tuning, validating, optimizing, visualizing, and debugging models in applied settings; familiarity with ML Ops concepts; experience in various coding environments and standard software engineering workflows
• An enthusiasm to ask questions and try and learn new things
• Entrepreneurial experience is desirable
• Experience in life sciences and healthcare and experience in a complex global organization is a plus

Education

• A track record of advanced degree in relevant fields (M.S., PhD) with substantial hands-on ML experience