Master’s degree in Linguistics, Computational Linguistics, or other language or data-related disciplines
2+ years experience with human data collection studies
Proficiency in Python
Experience with language data analysis
Experience with command-line environments (e.g. Unix) and version control (e.g. Git)
Experience in developing and evaluating data annotation metrics
The Bedrock AI Data Team in Amazon Web Services (AWS) is looking for a Language Engineer to collaborate in developing solutions for natural language data collections. This position is an opportunity to apply your expertise in a challenging but supportive environment.
The mission of the Bedrock AI Data Team is to engineer the datasets critical to the success of AWS’s Bedrock services. From human evaluations to Responsible AI safeguards to Retrieval-Augmented Generation and beyond, these products make Generative AI enterprise-ready and safe for users, impacting millions of people every day. We are a group of language engineers, linguists, data scientists, data engineers, and program managers, and we partner closely with the science, engineering, and product teams. We are customer obsessed and committed to delivering results with the highest quality and integrity.
As a Language Engineer, you will start by diving deep into a couple of critical projects for Bedrock services to drive these projects forward. You will collaborate with fellow language data scientists, program managers, as well as stakeholders in science, engineering, and product teams to understand the role data plays in developing models that meet customer needs. You will analyze, follow, and improve processes for collecting and annotating LLM inputs and outputs, assessing data quality, and automating where appropriate.
You will then expand your scope by using the principles of data-centric AI to understand the role our data plays with regard to model performance specifically, as well as the larger ML pipeline. You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language data scientists and scientists to design and implement principled strategies for data optimization.
Key job responsibilities
- Source, validate, and deliver high-quality language artifacts and linguistic data
- Collaborate with stakeholders to design data collection and development efforts
- Oversee the progress and quality of several data collection and annotation projects at a time
- Advocate for strict adherence to data collection guidelines and quality thresholds
- Extend existing data collection, annotation, and quality assurance efforts to support feature and language expansion
- Innovate on data collection methodologies, guidelines, quality metrics to support new requests
- Automate repetitive workflows and improve existing processes
About the team
The Bedrock AI Data Team at AWS is responsible for delivering high-quality annotated data and a variety of language artifacts to ensure the best performance of different AWS LLM services. These Generative AI services enable customers to readily add intelligence to their business operations and AI applications to drive positive outcomes.
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Hybrid Work
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.
Experience in statistical analysis/statistical modeling
Experience with machine-learning approaches in NLP
Comfortable working in a fast paced, highly collaborative and dynamic work environment
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.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $51,000/year in our lowest geographic market up to $114,100/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.
