Artificial Intelligence Engineer

Key Responsibilities

• Design, build, and optimize RAG pipelines, including prompting, text chunking, retrieval, reranking, and evaluation using vector databases such as Chroma DB or Qdrant, and Transformer-based LLMs like Llama, Mistral, or BERT family models.
• Productionize ASR systems (e.g., Whisper-large-v3) for call centre and voice-based use cases, ensuring improvements in both accuracy and latency.
• Develop OCR and document digitization workflows using tools such as OpenCV and Tesseract, along with CNN/LSTM-based post-processing for unstructured PDFs and images.
• Build and deploy APIs using Fast API or Flask, integrating with existing services and data sources such as MongoDB.
• Orchestrate data and model workflows using Airflow, automating ETL processes, evaluation pipelines, and periodic retraining.
• Implement CI/CD pipelines for model and API releases, ensuring strong testing, logging, and observability practices....