Job Overview We are seeking an AI Innovation Specialist to join our team and contribute to the development of innovative AI solutions in the life sciences domain. Key Responsibilities 1. Collaborate with stakeholders to design and develop generative AI solutions addressing pharma and healthcare applications. 2. Fine-tune pre-trained foundation models and work closely with stakeholders on analysis and implementation. 3. Translate machine learning research expertise into viable prototypes focused on human data, applying a thorough understanding of complex systems and interactions. 4. Develop model features for individual projects/products with guidance from experienced professionals. 5. Broaden knowledge of new algorithm creation by working alongside Machine Learning Engineers and Scientists. 6. Build and train production-grade algorithms to uncover patterns in large-scale, high-dimensional data, leveraging advanced statistical techniques. 7. Apply various optimization methods to enhance natural language processing and machine learning algorithm performance, driving innovation in AI-driven applications. 8. Evaluate model viability for deployment with stakeholder support, ensuring effective collaboration and problem-solving. 9. Consult with clients to implement innovative solutions, drive project delivery, and ensure successful client outcomes. Requirements 1. Possess a Master's Degree in Machine Learning, Statistics, Computer Science, Physics, Math, or a related field. 2. Demonstrate strong commercial awareness and a genuine interest in the healthcare industry. 3. Exhibit excellent project management, time management, and organizational skills, ensuring seamless workflow and productivity. 4. Hold 2-4 years of experience in creating machine learning algorithms, with a proven track record of delivering high-quality results. 5. Display proficiency in one or more programming languages: Java, C++, Python, R, Go, Kubernetes, Deep learning, or equivalent. 6. Showcase experience working with large real-world datasets, including data preprocessing, feature engineering, and model training.