Job Description
Amazon is seeking a Machine Learning Data Linguist to join our Alexa AI team. This role focuses on language data, primarily in the areas of text annotation and general data analysis deliverables.
The ML Data Linguist must have a passion for data, efficiency, accuracy, and should be capable of:
- Handling unique data analysis requests from a range of data customers
- Providing data quality expertise to other team members and coaching improvements
- Delivering high quality work in a fast-paced environment
- Working autonomously with minimum direction
- Building a thorough understanding of conventions and providing support to global sites
- Understanding changes to conventions deployed in response to customers' requests and modifying workflows accordingly
- Contributing to process improvements to reduce handling time and improve output
- Improving software tools by identifying bugs and suggesting enhancements
- Diving deep into issues and implementing solutions independently
- Proactively addressing issues and problems
- Keeping up with changing project conventions and priorities
Key job responsibilities
- Label, generate, and ensure the quality of datasets.
- Work closely with ML Data Linguists and scientists to understand data ambiguities and resolve issues in annotation guidelines.
- Conduct in-depth qualitative error trend analysis, developing action plans to enhance data quality.
- Collaborate with ML Data Linguists, scientists, and Ops Managers to drive innovation in processes, tracking, and annotation workflows.
A day in the life
Most days are spent collecting requirements from customers, collaborating with peers and stakeholders to complete deliverables, and recommending process improvements.
About the team
The work that we do is confidential, but we are a highly collaborative team who obsess over our internal and external customers.
Numbers & Facts
| Location | Seattle, WA |
| Industry | Retail |
| Company Size | 10,000 employees or more |
| Year Founded | 1994 |
| Website | http://Amazon.com/militaryroles |
About Company
At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.
Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.
It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here
Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.
It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here
Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
Skills
- Amazon Alexaunmatched
- Artificial Intelligence (AI)unmatched
- Coachingunmatched
- Customer/Client Researchunmatched
- Data Analysisunmatched
- Data Qualityunmatched
- Data Setsunmatched
- Divingunmatched
- Linguisticsunmatched
- Machine Learningunmatched
- Operations Managementunmatched
- Problem Solving Skillsunmatched
- Process Improvementunmatched
- Productivity Managementunmatched
- Qualitative Analysisunmatched
- Software Debuggingunmatched
- Team Playerunmatched
- Time Managementunmatched
- Trend Analysisunmatched
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