Language Engineer

Description

The Amazon Artificial General Intelligence (AGI) Data Services organization is dedicated to creating a wide array of datasets essential for training and evaluating Amazon's advanced AI models. We are actively seeking Language Engineers to join our innovative science and engineering team. In this role, you will contribute to the development of sophisticated, multimodal datasets, employing diverse methodologies such as synthetic data generation, model-assisted data creation, and human-in-the-loop data collection processes.

You will be instrumental in fostering innovation and pushing the boundaries of AI model evaluation and training. Collaborating closely with product managers, engineers, and data scientists across various teams, you will ensure our AI systems achieve and maintain best-in-class performance.

Key Job Responsibilities

• Design intricate data collection projects involving human participants, aligning with scientific objectives. This includes authoring clear instructions, establishing and implementing quality targets and mechanisms, providing day-to-day coordination of data collection (encompassing planning, scheduling, and reporting), and taking responsibility for final deliverables.
• Develop and execute complex data creation tasks utilizing synthetic and model-based generation techniques, adhering to state-of-the-art methodologies.
• Analyze and derive meaningful insights from extensive datasets.
• Construct tools or prototypes for data analysis and creation, leveraging Python or other scripting languages.
• Employ modeling tools to initiate or test new AI functionalities.
• Partner with scientists, software engineers, and other data creators to assess the performance of AI models.

About the Team

Amazon is committed to becoming the world's most customer-centric company, empowering customers to research and purchase a vast range of products online and offline. We set ambitious goals and seek individuals who can help us achieve and surpass them. The AGI organization is responsible for delivering AI capabilities across various Amazon products and search functions. We offer secure, flexible, cost-effective, and high-quality data development services to our clients, enabling them to build cutting-edge ML models.

Basic Qualifications

• Proven experience in managing and executing language data collection projects, including the development of guidelines, label sets, and annotation workflows.
• A Master's degree or higher in a relevant field, such as Computational Linguistics or a related discipline with a strong computational analysis component.
• A minimum of 2 years of experience in computational linguistics, language data processing, or AI data creation.
• Familiarity with language data annotation systems and various data markup techniques.
• Proficiency in scripting languages like Python.
• Experience working with speech, text, and multimodal data across multiple languages.
• Exceptional communication skills, strong organizational abilities, and meticulous attention to detail.
• Adaptability and comfort working in a fast-paced, highly collaborative, and dynamic environment.

Preferred Qualifications

• A PhD in Computational Linguistics or a related field with a significant computational emphasis.
• Expertise in initiating AI data collections for rapidly evolving requirements, particularly for complex agentic functions.
• Practical experience with Machine Learning and technical concepts, including APIs.
• Working knowledge of version control, agile development, database queries, and data analysis processes (e.g., SQL, R, Matlab).
• Demonstrated ability to think creatively, coupled with strong analytical and problem-solving skills.

Our inclusive culture empowers Amazonians to achieve outstanding results for our customers. If you require workplace accommodations due to a disability during the application or hiring process, including support for interviews or onboarding, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. For regions not listed, please contact your Recruiting Partner.