Applied Scientist, PXT Job-Person Matching
3 days ago
Job ID: 2911147 | Amazon Development Centre (Scotland) Limited
Do you want a role with deep meaning and the ability to make a massive impact? Hiring top talent is not only critical to Amazon’s success—it can literally change the world. It took a lot of great hires to deliver innovations like AWS, Prime, and Alexa, which make life better for millions of customers around the world every day. As part of the Intelligent Talent Acquisition (ITA) team, you'll have the opportunity to reinvent the hiring process and deliver unprecedented scale, sophistication, and accuracy that Amazon's Talent Acquisition operations need.
ITA is an industry-leading people science and technology organization made up of scientists, engineers, analysts, product professionals and more. Our shared goal is to fairly and precisely connect the right people to the right jobs. Last year, we delivered over 6 million online candidate assessments, replacing the "game of chance" with a merit-based approach that gives candidates the chance to showcase their true skills. Each year we help Amazon deliver billions of packages around the world by making it possible to hire hundreds of thousands of associates in the right quantity, at the right location and at exactly the right time. You’ll work on state-of-the-art research, advanced software tools, new AI systems, and machine learning algorithms to solve complex hiring challenges. Leveraging Amazon's in-house tech stack built on AWS, you'll have the autonomy and flexibility to bring innovative solutions to life. Join ITA in using technologies to transform the hiring landscape and make a meaningful difference in people's lives. Together, we can solve the world's toughest hiring problems.
The team for this position focuses on AI/ML based products to provide recommendations for job seekers at Amazon and building tools to better empower our recruiters to find bar raising talent. This team's science and engineering work is a key component in scaling the recruiting process to the over 20 million applications we get each year that result in the hiring of tens of thousands of Amazonians across the globe. We do this by utilizing both well-defined, established scientific research in the matching domain along with novel techniques developed by the team.
We are looking for AI/ML scientists who can delight our customers by continually learning and inventing, and who want to use their expertise to solve real business problems. Familiarity with natural language processing, two-tower embedding models, and experience with the science associated with recommendation and matching would be ideal, but there will be opportunities to learn these skills on the job as long as you have a strong scientific foundation to build from, experience in statistical analysis, and expertise in model building.
Key job responsibilitiesYou will work as an ML scientist in a team of other scientists and software developers. You will write scientific research for audiences with a range of scientific experience. You will routinely serve as the scientific advisor to the engineering and product teams to ensure the business and engineering choices are well supported by science.
You will be contributing regularly to the code base as this is an applied role with the expectation of 50% of your time spent coding. You will primarily be writing code in Python and will be using the latest technologies including AWS. Your solutions will meet high standards of performance and reliability, and will operate at massive scale.
A day in the lifeAs an applied scientist working at Amazon, you will play a key role in identifying business opportunities, measuring opportunity, researching and prototyping solutions. You will use a wide range of technologies, programming languages and systems. You will work closely with an experienced engineering and product team. You will have the ability and encouragement to explore your own ideas and the reward of seeing your contributions benefit millions of customers worldwide.
About the teamThe team - internally known as Sorting Hat - is full of talented people who come from all over the world. The team is made up of experienced Software Development Engineers and Applied Scientists, and we are supported by a great product team and research science team. We have ready access to senior engineers and scientists enabling a great learning environment for new Amazonians.
We are primarily based in Edinburgh, Scotland and works closely with other hybrid science/engineering teams located in the centre.
BASIC QUALIFICATIONS- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Experience programming in Java, C++, Python or related language
- Experience researching about machine learning, deep learning, NLP, computer vision, data science
- Experience building machine learning models or developing algorithms for business application
- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice to know more about how we collect, use and transfer the personal data of our candidates.
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 our accommodations page for more information.
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