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Role Description
This role involves building language pipelines for classification, retrieval-augmented generation (RAG), and tokenization. You’ll design robust text analytics and evaluation frameworks that scale across multilingual corpora, powering advanced AI-driven systems.
- Build NLP pipelines for classification, tokenization, and RAG tasks
- Design scalable text analytics workflows that support multilingual datasets
- Implement and fine-tune models with Hugging Face Transformers, PyTorch, and fastText
- Develop evaluation frameworks for model performance across diverse corpora
- Integrate NLP solutions into broader AI pipelines, including search and retrieval systems
- Collaborate with AI researchers and engineers to ship robust, production-grade NLP systems
Qualifications
- Have a background in computer science, computational linguistics, or related fields
- Proficient with Hugging Face Transformers, spaCy, tokenizers, and PyTorch
- Experience working with text formats like JSON/JSONL and building scalable data pipelines
- Understand NLP tasks such as classification, entity recognition, tokenization, and retrieval
- Comfortable working with multilingual corpora and designing evaluation benchmarks
- Strong experience with text preprocessing, embedding generation, and model fine-tuning
- Curious about building RAG systems and neural search pipelines that combine IR and NLP
Requirements
- Design and ship NLP pipelines for classification, tokenization, and RAG that can handle large-scale, multilingual corpora
Benefits
- Classified as an hourly contractor to Mercor
- Paid weekly via Stripe Connect, based on hours logged
- Part-time (20–30 hrs/week) with flexible hours—work from anywhere, on your schedule
- Weekly Bonus of $500–$1000 USD per 5 tasks
- Remote and flexible working style
Company Description
Mercor is hiring an NLP Engineer on behalf of a leading AI lab.
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