Ai Ml Engineer

AI/ML Engineer with 2-3 years of experience

Key Responsibilities:

• Design, develop, and implement machine learning, deep learning, and LLM-based models.
• Work on data preprocessing, feature engineering, vectorization, and model optimization.
• Build and deploy RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
• Integrate AI solutions, APIs, and LLM workflows into existing applications and systems.
• Collaborate with data engineers and software developers to ensure seamless deployment.
• Conduct experiments and evaluate model performance using appropriate metrics.
• Stay updated with the latest advancements in AI/ML, GenAI, and LLM technologies.

Required Skills:

• Strong knowledge of Python

  and ML libraries such as TensorFlow, PyTorch, scikit-learn, or Keras.
• Hands-on experience with

  Hugging Face Transformers

  , model fine-tuning, and working with pre-trained LLMs.
• Experience building

  RAG pipelines

  , including embeddings, vector search, and chunking strategies.
• Familiarity with vector databases such as

  FAISS, Pinecone, Weaviate, Milvus, or ChromaDB

  .
• Experience with NLP, computer vision, or predictive analytics.
• Proficiency in data preprocessing using

  Pandas, NumPy

  , and related Python tools.
• Experience with REST APIs and model deployment (e.g.,

  Flask, FastAPI, Docker

  ).
• Understanding of cloud AI platforms (

  AWS, GCP, Azure

  ) and their ML services.
• Knowledge of SQL and NoSQL databases for data retrieval and feature engineering.
• Experience working with Git and collaborative development workflows.
• Basic understanding of MLOps practices, including model tracking, CI/CD, and containerization.
• Ability to optimize models for performance, latency, and scalability.
• Familiarity with data visualization tools (Matplotlib, Seaborn) for insights and reporting.
• Strong analytical, mathematical, and problem-solving skills.