FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Computational Linguistics and Natural Language Processing, with a strong focus on prompt design, dataset management, and model evaluation. Proficient in Python for data processing and automation, while effectively collaborating with cross-functional teams to enhance AI-driven language solutions.
Highest-signal resume keywords
Computational LinguisticsNatural Language Processing (NLP)Python ProgrammingPrompt Design and EvaluationDataset Management and Quality Assurance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Computational LinguisticsNatural Language Processing (NLP)Python ProgrammingDataset ManagementAnnotation WorkflowsEvaluation MethodsQuality AssuranceModel Behaviour AnalysisPrompt DesignData Processing
Soft Skills
CollaborationQualitative AnalysisQuantitative AnalysisProblem SolvingLinguistic Precision
Tools & Technologies
AI ToolsAutomation ToolsEvaluation ToolsData Annotation ToolsNLP Frameworks
Industry Keywords
Language TechnologyAI SystemsQuality Control ProcessesLinguistic PhenomenaLLM Research
Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Formalise linguistic phenomena into rules, taxonomies, annotation criteria, and system or model requirements
- Design, evaluate, and improve prompts and AI components for language-learning use cases
- Build datasets for training, calibration, and evaluation, including annotation guidelines and quality-control processes
- Evaluate model behaviour using qualitative and quantitative methods
- Investigate failure modes and quality issues and validate fixes across prompts, models, data, and downstream processing
- Use Python and existing tooling to process linguistic data and automate evaluation
- Collaborate with engineers, product managers, learning designers, and computational linguists
- Develop reusable solutions, resources, and practices that scale across use cases and languages
- Stay informed about advances and best practices in NLP and LLM research
Requirements
What you’ll need- 2–3 years of experience in Computational Linguistics, NLP, or a related role
- Hands-on experience working with LLMs, including prompt design, evaluation, and model behaviour analysis
- Proficiency in Python for data processing, evaluation, and automation
- Strong understanding of datasets, annotation workflows, evaluation methods, and quality assurance for AI systems
- AI-native mindset and comfort using AI tools for problem solving, analysis, and workflow automation
- Strong qualitative and quantitative analysis skills
- Ability to collaborate effectively in cross-functional teams
- Degree in Linguistics, Computational Linguistics, NLP, Language Technology, or a related field, or equivalent practical experience
- Excellent command of English, spoken and written, with strong linguistic precision
Benefits
Comp & perks- A generous monthly allowance for lessons on Preply.com
- Learning & Development budget
- Time off for self-development
- Competitive financial package with equity
- Leave allowance
- Health insurance
- Access to free mental health support platforms
- Open, collaborative, dynamic, and diverse culture
