Leena AI

Machine Learning Engineer

Gurugram, HR, IN

5 months ago
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Summary

Job Description

We are seeking a talented and experienced Machine Learning Engineer with a strong focus on Natural Language Processing (NLP). You will play a key role in developing, optimizing, and deploying state-of-the-art NLP solutions. You will collaborate with cross-functional teams to design scalable AI-driven applications that leverage the latest advancements in machine learning.

Key Responsibilities

  • Design, develop, and implement NLP models using modern techniques like BERT, GPT, and other LLMs.
  • Fine-tune pre-trained models for specific NLP applications, text summarization, and question-answering systems.
  • Research and experiment with cutting-edge ML techniques and optimize model performance.
  • Collaborate with product managers and software engineers to create end-to-end solutions that scale in production.
  • Evaluate and improve model accuracy, scalability, and performance using appropriate metrics.
  • Stay updated on the latest trends in NLP and machine learning to implement best practices.

Required Skills And Qualifications

  • 3-6 years of experience in machine learning with a focus on NLP
  • Hands-on experience with BERT and other transformer models
  • Proficiency in working with large language models (e.g., GPT, T5, etc.)
  • Strong programming skills in Python, with experience in ML libraries like PyTorch, Hugging Face
  • Deep understanding of tokenization, embeddings, sequence-to-sequence models, and attention mechanisms
  • Experience with fine-tuning models for specific use cases
  • Familiarity with data preprocessing techniques for NLP tasks
  • Experience with ML Serving for deploying models at scale
  • Strong problem-solving skills and ability to work in a fast-paced environment

Skills: embeddings,data preprocessing techniques,ai fundamentals,machine learning,gpt,design,natural language processing (nlp),sequence-to-sequence models,pytorch,tokenization,python,bert,nlp,large language models (llms),attention mechanisms,models,hugging face

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