Principal Applied Scientist, Amazon Special Projects
About The Position
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. We are seeking a Principal Applied Scientist working on machine learning applications in life sciences. This role combines scientific leadership with hands-on innovation, driving solutions from exploratory research through production-ready solutions deployment, while maintaining high scientific standards. You will work with Amazon's large-scale computing resources to accelerate advances in machine learning applications.
Requirements
- Deep expertise in machine learning, with broad knowledge across biology and life science.
- Strong understanding of scientific methodologies and experimental design.
- Ability to develop production-level code and systems.
- Track record of working with cross-functional scientific teams and fostering collaboration.
- 10+ years of relevant, broad research experience after a PhD degree in computer science, computational biology or relevant field .
- Experience with deep learning frameworks (PyTorch, TensorFlow).
- Familiarity with high-performance computing environments.
- Experience with ML for science and structural biology tools.
Responsibilities
- Lead ML for life science efforts using computational design approaches and ML-based tools.
- Guide teams in applying SOTA ML methods, experimentation design, and modeling approaches.
- Transform complex real world problems into scientific challenges and allocate resources effectively.
- Review requirements, conduct technical architecture reviews, and make informed judgments around technical and business tradeoffs.
- Provide mentorship to Applied Scientists, Research Scientists and Data Scientists while maintaining scientific rigor.
- Collaborate with cross functional teams.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
Ph.D. or professional degree
Number of Employees
5,001-10,000 employees
