Do you want to be part of an inclusive team that works to develop innovative therapies for patients? Every day, we are driven to develop and deliver innovative and effective new medicines to patients and physicians.  If you want to be part of this exciting work, you belong at Astellas!

Astellas Pharma Inc. is a pharmaceutical company conducting business in more than 70 countries around the world. We are committed to turning innovative science into medical solutions that bring value and hope to patients and their families. Keeping our focus on addressing unmet medical needs and conducting our business with ethics and integrity enables us to improve the health of people throughout the world. For more information on Astellas, please visit our website at www.astellas.com.

Purpose:

We are seeking an experienced Machine Learning Engineer to join our team and play a transformative role in advancing machine learning initiatives at Astellas. In this high-impact position, you will contribute to the development of scalable, production-level machine learning solutions that drive significant business value and innovation within our organization.

As an expert in your field, you will collaborate with cross-functional teams to design, implement, and maintain advanced machine learning models. Your deep expertise in deep learning, statistical analysis, and rigorous testing will be crucial in ensuring the reliability and performance of our machine learning systems in a production environment.

This role offers the opportunity to make substantial contributions to transformative projects that shape the future of machine learning at Astellas. While experience with generative AI is a plus, we are primarily seeking professionals with a strong foundation in machine learning who are passionate about driving meaningful change.

 

Essential Job Responsibilities:

Design and Develop Machine Learning Models: Create and deploy machine learning and deep learning models that are robust, efficient, and scalable for production use. Production-Level Development: Integrate machine learning models into existing software systems, ensuring seamless deployment and operation in a production setting. Scalable Solutions: Architect solutions that can handle large-scale data and high throughput demands, optimizing for performance and resource utilization. Statistical Analysis and Modeling: Apply statistical methods to analyze data, validate models, and interpret results to inform decision-making processes. Testing and Validation: Implement comprehensive testing strategies, including unit tests, integration tests, and performance tests, to ensure model reliability and accuracy. Data Preprocessing and Feature Engineering: Process and analyze large datasets to extract meaningful features that enhance model performance. Collaboration: Work closely with data scientists, software engineers, and product managers to understand requirements and deliver solutions that meet business objectives. Documentation: Maintain clear and detailed documentation of methodologies, code, and processes to facilitate knowledge sharing and compliance.