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.
As an applied scientist on our team, you will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, define the science vision and translate it into specific plans for applied scientists, as well as engineering and product teams. You will partner with scientists, economists, and engineers on the design, development, testing, and deployment of scalable ML and econometric models. This is a unique, high visibility opportunity for someone who wants to have impact, dive deep into large-scale solutions, enable measurable actions on the employee experience, and work closely with scientists and economists. This role combines science leadership, organizational ability, and technical strength.
Key job responsibilities
As an Applied Scientist, ML Applications, you will:
• Lead applied scientists to deliver machine-learning and AI solutions to production.
• Design, develop, and evaluate innovative machine learning solutions to solve diverse challenges and opportunities for Amazon customers
• Advance the team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner.
• Partner with the engineering team to deploy your models in production.
• Partner with scientists from across PXTCS to solve complex problems and use your team’s expertise to accelerate their ability get their work into production.
• Work directly with Amazonians from across the company to understand their business problems and help define and implement scalable ML solutions to solve them.
• Mentor and develop junior scientists and developers.
We are open to hiring candidates to work out of one of the following locations:
Austin, TX, USA | Chicago, IL, USA | Seattle, WA, USA
- Master's Degree in machine learning, recommender systems, statistics, computer science, operations research, or other highly relevant field
- Five or more years’ experience applying ML to solve complex problems for large-scale applications
- Two or more years of experience specifically with deep learning (e.g., CNN, RNN, LSTM)
- Experience in using Python or other programming languages
- Ph.D. in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a closely related field.
- Experience delivering as part of cross-disciplinary teams.
- Hands on experience developing ML models with deep learning frameworks and building production pipelines on the cloud.
- 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.
- Experience with generative AI.
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. Applicants should apply via our internal or external career site.