Artificial Intelligence Engineer - Gurgaon / Gurugram - Globiva

    Globiva
    Globiva Gurgaon / Gurugram

    2 days ago

    Full time ₹900,000 - ₹2,200,000 (INR) per year *
    Description

    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.
    • Manage both offline and online evaluation for metrics such as latency, accuracy, F1 score, ASR WER, and retrieval precision/recall, and provide detailed analytical reports and recommendations.
    • Collaborate closely with product and operations teams to translate business challenges into measurable ML objectives and service-level agreements (SLAs).

    Must-Have Skills

    • Proficiency in Python (production-grade), PyTorch, and Hugging Face Transformers.
    • Strong understanding of RAG fundamentals, including text chunking, embedding selection, retrieval (dense and sparse), reranking, and evaluation frameworks.
    • Experience with vector search and data stores such as Chroma DB or similar technologies, along with solid data modelling and indexing expertise.
    • Practical knowledge of API development using Fast API or Flask, including RESTful best practices, authentication, rate limiting, and pagination.
    • Experience in MLOps using Docker, CI/CD, Linux, Git, and tools for logging and monitoring model services.
    • Exposure to OCR and ASR systems, particularly OpenCV, Tesseract, and Whisper (or equivalent frameworks).
    • Strong grasp of classical NLP and ML techniques, including tokenization, LSTMs/CNNs, XGBoost, and metric-driven experimentation.

    Good-to-Have Skills

    • Experience fine-tuning large language models or encoders for classification, summarization, and domain adaptation.
    • Understanding of prompt engineering, tool integration, and evaluation for LLM-based applications.
    • Familiarity with scaling retrieval systems for low-latency, high-availability production environments.
    • Experience with document question answering, email or call centre analytics, or enterprise knowledge management.
    • Knowledge of agentic AI frameworks such as Lang Chain, Lang Graph, or Crew AI.

    Qualifications

    • 3-6 years of hands-on experience in AI, ML, or NLP engineering with proven production ownership.
    • Bachelor's degree in computer science, or a related field, or equivalent practical experience.
    • Strong portfolio or GitHub profile demonstrating shipped APIs, model implementations, and well-documented repositories with test coverage.
    * This salary range is an estimation made by beBee
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