Computational Linguist with Gen AI experience
About The Position
We’re looking for a versatile Computational Linguist to join our R&D team focused on evaluating and supporting Generative and Agentic AI systems. This role combines linguistic expertise, data analysis, and hands-on experimentation with large language models. You’ll help design annotation workflows, create and refine guidelines and internal documentation, prototype task-specific evaluation metrics, configure annotation tools, and analyze annotator, model and system performance using real-world data, contributing to papers and articles as needed. The ideal candidate should demonstrate technical leadership in driving complex projects from concept to delivery. This is a hybrid linguistics + data science role: ideal for someone who can move between qualitative language analysis and quantitative evaluation. You’ll work cross-functionally with researchers and annotators to design innovative, rigorous, and scalable evaluation processes for LLM-powered workflows.
Requirements
- Master’s degree (or equivalent experience) in Computational Linguistics, NLP, Linguistics, or a related field
- 2+ years of experience in NLP or AI projects (industry or research)
- At least one year of experience with Gen AI and/or Agentic AI
- Experience using and fine-tuning transformer-based language models (e.g., BERT, GPT)
- Proficiency in Python programming
- Proficient with NLP and data science libraries: pandas, numpy, scikit-learn, NLTK
- Experience with generative AI SDKs and frameworks (e.g., OpenAI, Google, Anthropic, LangChain)
- Comfortable with Linux environments and Bash scripting
- Experience working with public datasets (e.g. Hugging Face, Kaggle)
- Familiarity with LLM behavior, prompt-based evaluation, and generative model outputs
- Comfortable with structured data formats (JSONL, CSV), Jupyter notebooks, and pandas-based analysis
- Experience using Git for version control and collaborative development
- Understanding of model evaluation methodologies, including human-AI comparison and red teaming
- Strong written communication skills for documenting experiments and results
- Experience working in cross-functional or research-oriented teams
- Fluent in English
Nice To Haves
- Strong understanding of current trends and techniques in generative AI
- Experience with annotation tools (e.g., Label Studio, Prodigy) and quality metrics for human data
- Experience designing annotation tasks and workflows (e.g., Label Studio or similar tools)
- Experience creating and curating bespoke datasets
- Familiarity with evaluation challenges in creative or subjective NLP tasks
- Understanding of linguistic typology, multilingual NLP, or sociolinguistic variation
- Experience working in WSL environments
- Experience collaborating with annotation teams and working with QA processes
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
251-500 employees
