Principal, Applied Scientist , People eXperience Technology Central Science (PXTCS)Job ID: 2849247 | Amazon.com Services LLC
Do you want to use your expertise in translating innovative science into impactful products to improve the lives and work of over a million people worldwide? If you do, People eXperience Technology Central Science (PXTCS) would love to talk to you about how to make that a reality.
PXTCS is an interdisciplinary team that uses economics, behavioral science, statistics, and machine learning to identify products, mechanisms, and process improvements that both improve Amazonian's wellbeing and their ability to deliver value for Amazon's customers. We work with HR teams across Amazon to make Amazon PXT the most scientific human resources organization in the world.
You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization.
You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.
You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modeling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends.
You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads.
You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences.
Key job responsibilitiesYou will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).
BASIC QUALIFICATIONS- Master's Degree in machine learning, recommender systems, statistics, computer science, operations research, or other highly relevant field
- Ten or more years' experience applying ML to solve complex problems for large-scale applications
- Five or more years of experience specifically with deep learning (e.g., CNN, RNN, LSTM)
- Proficient in using Python or other programming languages
- Hands-on experience developing ML models with deep learning frameworks and building production pipelines on the cloud.
- Experience with generative AI.
PREFERRED QUALIFICATIONS- Ph.D. in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a closely related field.
- Proven track record of delivering as part of cross-disciplinary teams.
- Strong communication and presentation skills.
- Comfortable working in a fast paced, highly collaborative, dynamic work environment.
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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