🌟 Join Sigma.AI – Shaping the Future of Artificial Intelligence 🌍

🔹 What is Sigma?

Sigma is a leading global technology company specializing in data collection and annotation for Artificial Intelligence. With over 30 years of experience, offices in Spain, the United States, and the United Kingdom, and operations in more than 700 languages, we support multinational clients in developing cutting-edge AI solutions.

👍 Soft Skills We Value:

Are you a proactive professional who enjoys challenges, values collaboration, and approaches every task with empathy, integrity, and a passion for learning?

If so, we’d love to hear from you!

💼 About the Role:

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

🚫 Important Notes:

Sigma.AI does not hire through third parties. No agents’ intermediaries or third parties are authorized to represent benefit from or participate in any way in the relationship. To this effect the Candidate agrees to provide any documentation or information reasonably requested by the Company to verify their identity and credentials. Should the Candidate fail to provide enough evidence of their identity to Sigma's satisfaction, Sigma shall be entitled to withhold or terminate any offer with the Candidate.

The company may employ or rely on artificial intelligence systems in its selection processes. Such processing is carried out in an ethical, transparent, and legally compliant manner. The purpose of the processing is to evaluate the tests submitted in the course of the selection process (for instance the transcribed content provided by the candidate). The legal basis for processing your data is the pre-contractual relationship between the parties and/or the provision of requested services.

💬 Need Help?

We’re here for any questions or concerns.

Join us and be part of something global, innovative, and impactful.

Sigma.AI – Data done right.