Are you passionate about machine learning algorithms? Do you want to drive the innovation in science and ML models behind real-world large scale recommendation systems? Do you want to impact what is shown to Amazon customers across the website by innovating with Amazon scale data? We are looking for a passionate scientists to lead the science charter of our centralized recommendations and multivariate optimization services team. Our team focuses on optimizing the customer experience on Amazon.com primarily through content and media recommendations. We operate a central service for ranking and optimization decisions as well as the backend infrastructure and algorithms to support these decisions.

We’re seeking an Applied Scientist to develop AI solutions to recommend the right content in the right format to customers at the right time. We are looking for individuals with a passion for learning, researching, and deploying production-ready science solutions in a highly collaborative environment. We like to ideate, experiment, iterate, optimize and scale quickly, while thoughtfully balancing speed and quality

Key job responsibilities
- Research, design, and implement recommendation systems that personalise across different customer experience touch points.
- Collaborate with engineers to deploy and integrate successful model experiment results into large-scale, complex Amazon production systems with low latency.
- Provide machine learning thought leadership to both technical and business leaders, with the ability to think strategically about business, product, and technical challenges.
- Define the science roadmap and research agenda that aligns with the organisation's priorities
- Work with technical product managers to work backwards from what's important to customers and deliver ML backed solutions.
- Report and share results with the team and wider scientific community by authoring documents that are both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.

BASIC QUALIFICATIONS

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

PREFERRED QUALIFICATIONS

- Experience in professional software development
- Experience in patents or publications at top-tier peer-reviewed conferences or journals

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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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 $223,400/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. This position will remain posted until filled. Applicants should apply via our internal or external career site.