Sigma AI is a global training data collection, preparation and annotation services company. With 30+ years of experience in the data annotation space, we support companies with the right mix of people, processes and technology to train smarter AI that serves humans better.

We're looking a Senior Computational Linguist to collaborate with the Natural Language Processing team on the design and development of AI-based solutions for clients and grant-funded projects. 
Candidates should feel comfortable working in a young and multidisciplinary team where the environment is continuously changing.

About the Job 

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.  

Required Qualifications 

• 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 

Preferred Qualifications 

• 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