Data Architect

2 days ago

Ahmedabad, Gujarat, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Opportunity

We are seeking a skilled Data Scientist & AI Engineer who is passionate about solving real-world problems using data, machine learning, and cutting-edge AI technologies.

This role offers the opportunity to work on advanced predictive modeling, Generative AI, and Natural Language Processing (NLP), while collaborating with cross-functional teams to deliver innovative solutions.

Key Responsibilities

  • Design, develop, and deploy predictive models and machine learning algorithms for classification, regression, and clustering.
  • Build and optimize Retrieval-Augmented Generation (RAG) pipelines and scalable systems using large language models (LLMs).
  • Fine-tune and customize LLMs to align with specific business use cases.
  • Explore and evaluate open-source LLMs to stay ahead of emerging AI advancements.
  • Apply traditional NLP techniques (e.g., BERT, text classification, sentiment analysis, NER).
  • Develop and maintain APIs for AI models using frameworks such as FastAPI, ensuring scalability and reliability.
  • Collaborate with data scientists, product managers, and engineers to integrate AI-driven features into products.
  • Perform data preprocessing, feature engineering, and validation for ML/AI models.
  • Document solutions and communicate insights clearly to both technical and business stakeholders.
  • Continuously improve models, pipelines, and analytics processes.

Required Skills and Qualifications

  • Strong programming skills in Python with libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn.
  • Solid experience with SQL for data extraction and transformation.
  • Hands-on experience building and tuning supervised & unsupervised ML models.
  • Understanding of model evaluation metrics (accuracy, precision, recall, F1-score, ROC-AUC).
  • Familiarity with GenAI concepts and production-grade implementation.
  • Exposure to traditional NLP or recommendation systems is a plus.
  • Knowledge of data engineering practices including cleaning, transformation, and pipeline automation.
  • Experience with version control tools (Git) and Jupyter notebooks.

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