Language Engineer, Artificial General Intelligence - Data Services

Amazon; Cambridge; On-site; GBP 40,000 - 60,000; Full time

Job summary

A leading technology company in the UK is seeking a Language Engineer to develop multimodal datasets for training advanced AI models. This role involves designing data collection processes, analyzing large datasets, and working collaboratively with engineers and scientists. The ideal candidate holds a Master's degree in Computational Linguistics, has experience in language data processing, and is proficient in Python. Applicants should exhibit strong organizational skills and be comfortable in a fast-paced environment.

Qualifications

• Master's degree in Computational Linguistics or equivalent.
• 2+ years experience in computational linguistics or AI data creation.
• Experience with language data annotation systems.

Responsibilities

• Design complex data collections with human participants.
• Analyze and extract insights from large datasets.
• Collaborate with scientists and engineers in AI model evaluation.

Skills

Computational linguistics

Scripting (Python)

Data analysis

Data collection design

Communication

Organizational skills

Education

Master's or higher in Computational Linguistics

Tools

SQL

R

Matlab

Job description

Description

The Amazon Artificial General Intelligence (AGI) Data Services organization is responsible for developing diverse datasets to train and evaluate the Amazon AI models. We are looking for Language Engineers to join our science and engineering team to support the development of complex, multimodal datasets, using a range of approaches including synthetic data generation, model-supported data generation, and human-in-the-loop data collections.

You will play a critical role in driving innovation and advancing the state-of-the-art in evaluating and training AI models. You will work closely with cross-functional teams, including product managers, engineers, and data scientists to ensure that our AI systems are best in class.

Key Job Responsibilities

• Design complex data collections with human participants in response to science needs: author instructions, define and implement quality targets and mechanisms, provide day-to-day coordination of data collection efforts (including planning, scheduling, and reporting), and be responsible for the final deliverables
• Design and conduct complex data creation tasks using synthetic and model-based data generation methods, following state‑of‑the‑art approaches
• Analyze and extract insights from large amounts of data
• Build tools or tool prototypes for data analysis or data creation, using Python or another scripting language
• Use modeling tools to bootstrap or test new AI functionalities
• Collaborate with scientists, software engineers, and other data creators to evaluate performance of AI models

Basic Qualifications

• Master's or higher degree in a relevant field (Computational Linguistics or equivalent field with computational analysis)
• 2+ years experience in computational linguistics or language data processing or AI data creation
• Experience with language data annotation systems and other forms of data markup
• Proficient with scripting languages, such as Python
• Experience working with speech, text, and multimodal data in multiple languages
• Excellent communication, strong organizational skills and very detail oriented
• Comfortable working in a fast paced, highly collaborative, dynamic work environment

Preferred Qualifications

• PhD in Computational Linguistics (or equivalent field with computational emphasis)
• Expertise in bootstrapping AI data collections for quickly evolving requirements
• Extensive experience working with speech, text, and multimodal data in multiple languages
• Experience in data creation for complex agentic workflows
• Practical experience with Machine Learning
• Familiarity with technical concepts such as APIs
• Practical knowledge of version control and agile development
• Familiarity with database queries and data analysis processes (SQL, R, Matlab, etc.)
• Willingness to support several projects at one time, and to accept reprioritization as necessary
• Able to think creatively and possess strong analytical and problem solving skills

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