Key Responsibilities:

• Develop NLP pipelines for NER, classification, relation extraction, and summarization.
• Build RAG systems to enable domain-specific question answering and search.
• Maintain scalable document indexing and vector retrieval systems.
• Normalize unstructured data using OCR + layout-aware processing.
• Fine-tune and evaluate transformer-based models (BERT, RoBERTa, custom LLMs).
• Implement orchestration with tools like Airflow or Dagster.
• Deploy APIs using Docker and support integration via CI/CD.
• Track experiments and models using MLflow or Weights & Biases.
• Collaborate with product teams to align AI features with real user workflows.

Minimum Requirements:

• MS or PhD in CS, Computational Linguistics, or related field with NLP focus.
• 2+ years developing production-grade NLP systems.
• Proficient in Python and libraries such as Hugging Face, spaCy, PyTorch, TensorFlow.
• Experience with search and vector tools (e.g., Elasticsearch, FAISS, Pinecone).
• Practical experience applying LLMs and retrieval-augmented generation.
• Must have experience at a tech company.
• Must have an active LinkedIn profile.

Preferred Experience:

• OCR and document layout parsing for scanned files.
• Fine-tuning transformers on niche datasets.
• Strong grasp of MLOps (Docker, CI/CD, model serving).
• Familiarity with human-in-the-loop learning or compliance-sensitive domains.

Why Join:

Join a high-impact team solving real problems with advanced NLP and LLMs. Enjoy aflexible, learning-driven culture, strong compensation, equity, and full benefits.