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Applied Scientist II, CMAX, Recruiting Engine

Job ID: 1773530 | Amazon Dev Center U.S., Inc.

DESCRIPTION

Job summary
Are you seeking a job where your work will have massive impact? Want to join a new team and build an awesome new product that will change people's lives? Come and be a pioneer and leader on a team that is building a product that will touch millions of job applicants annually.

Automated Questions is a new ML product being developed by CMAX within Recruiting Engine with the aim of helping Amazon recruitment become more effective, delivering a better candidate experience to the 26M+ job applicants annually. Automated Questions is a green-field product that will combine machine learning and process improvement to make a fundamental improvement to recruitment at scale within Amazon.

Automated Questions leverages the power of Artificial Intelligence and the large ecosystem of services such as Lambda, Amazon S3 and Amazon Kinesis to provide a hand-off-the-wheel, easy-to-use, extensible, and natural recruiter experience, while significantly enhancing the candidate:role discovery journey. With this technology, we will transform the way applicants find and apply for jobs at Amazon.

We have an exciting charter in front of us that includes solving highly complex scientific, engineering and algorithmic problems. We are looking for a passionate and talented Applied Scientist to join us and be a science leader for a team innovating to deliver this new service, addressing customer needs to build modern, user-focused product on our roadmap. This position offers a rare opportunity to be a part of a fast-growing product in the run-up to launch, and help shape the technology and product as we grow. You will be playing a crucial role in scientific discovery, developing, and enabling your team as they produce and support the product, with the opportunity to deliver scaleable, resilient systems while maintaining a constant customer focus.

Key job responsibilities
As an applied scientist on our team, you will leverage your strong background in Computer Science and Machine Learning to help build the next generation of our model development and assessment pipeline, harness and explain rich data at Amazon scale, and provide automated insights to improve machine learned solution that impact millions of job applicants annually. Your role will benefit from your pragmatic technical leadership, and you'll feel comfortable with ambiguity, be capable of summarizing complex data and models through clear visual and written explanations.

We are particularly interested in applicants with experience applying natural language processing, deep learning, and reinforcement learning at scale.
You will demonstrate strong rigor in applied sciences and engineering, creativity, curiosity, and great judgment.

Your responsibilities will include:
· Analyze the data and metrics resulting from traffic into Amazon's product search service.
· Design, build, and deploy an effective and innovative ML solutions to improve our discovery and classification
· Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.
· Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IR.

Please visit https://www.amazon.science for more information

A day in the life
Your team places value on work-life balance. Most days, the team is co-located in the office, but you're also flexible when people occasionally need to work from home. Generally, the team keep core in-office hours from 10am to 4pm. About half of the team come in earlier and the other half stay later.

Your daily routine will include meeting with leadership, and with the other individual contributors in the team to help support the individuals both in the development of the team's product, and in their own career development. You'll coach and mentor, create the mechanisms to ensure that operational excellence is maintained, and hold the team to account to ensure that standards are constantly driven higher.

You'll be working on a high-impact, high-visibility product, with your work improving the experience of millions of job applicants to Amazon.

On a daily basis, you'll have the opportunity to use (and innovate on) state-of-the-art ML methods to solve real-world problems.

You'll get excellent opportunities, and ample support, for career growth, development, and mentorship.

About the team
Our team is dedicated to supporting new team members. Our team has a broad mix of experience levels and Amazon tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our engineers, scientists, and leaders, truly enjoy mentoring and supporting one another, with a fully matrix-style support network. Everyone is a leader!

Our team is intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. We believe that an inclusive and welcoming culture help us build better services and better teams.

We’re looking for a new teammate who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers; someone who will help us amplify the positive & inclusive team culture we’ve been building.

BASIC QUALIFICATIONS

· PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
· 2+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language

PREFERRED QUALIFICATIONS

· Excellent technical, problem-solving and communication skills
· Experience as a coach and mentor to junior team members
· Experience delivering large scale software product releases
· Experience defining KPIs/SLAs


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.