Machine Learning Engineer

1 week ago

Gurugram, India CreateBytes Full time
Job Description: Machine Learning Engineer


Position: Machine Learning Engineer


Experience: 2+ years in NLP


Location: Gurgaon


Key Responsibilities:

  • Develop and implement NLP models using transformers, LLMs, and Generative AI/prompt engineering (RAG architecture).
  • Work with open-sourced LLMs such as Microsoft Phi, Mixtral, or Llama models.
  • Utilize data science tools including Python scripting, CUDA, numpy, and more for efficient data handling and processing.
  • Manage vector databases like ChromaDB and Pinecone.
  • Employ libraries such as scikit-learn, Hugging Face, LangChain, LlamaIndex, PyTorch, Keras, etc., for model development and fine-tuning.
  • Perform model fine-tuning on custom datasets, hyperparameter tuning, data collection, data preprocessing, ETL, and ELT.
  • Execute prompt engineering to enhance AI model performance.
  • Operate within cloud environments like Azure, GCP, or AWS and leverage ML frameworks like TensorFlow and PyTorch.
  • Apply standard ML algorithms including supervised learning, unsupervised learning, and deep learning networks like RNNs and CNNs.
  • Build and deploy RESTful APIs, serving them on virtual machines.


Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Minimum of 2+ years of experience in NLP and machine learning.
  • Proven experience with transformers, LLMs, and Generative AI.
  • Strong proficiency in Python scripting, CUDA, numpy, and other data science tools.
  • Knowledge and experience with vector databases (ChromaDB, Pinecone).
  • Expertise in using ML libraries such as scikit-learn, Hugging Face, LangChain, LlamaIndex, PyTorch, and Keras.
  • Skilled in model fine-tuning, hyperparameter tuning, and prompt engineering.
  • Familiarity with cloud environments (Azure, GCP, AWS) and ML frameworks (TensorFlow, PyTorch).
  • Solid understanding of standard ML algorithms and deep learning networks (RNNs, CNNs).
  • Experience in building and deploying RESTful APIs on virtual machines.
  • Excellent problem-solving skills and the ability to work in a collaborative team environment.


Preferred Qualifications:

  • Experience with open-sourced LLMs such as Microsoft Phi, Mixtral, or Llama models.
  • Knowledge of advanced data preprocessing techniques and ETL/ELT processes.
  • Strong understanding of AI ethics and data privacy considerations.


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