Large Scale AI/ML Engineer

3 days ago

Hyderabad, Telangana, India beBeeSenior Full time ₹ 90,00,000 - ₹ 1,25,00,000

Job Title: Senior Large Language Model Engineer

We are seeking a highly skilled and experienced Senior Large Language Model Engineer to join our team. The ideal candidate will have a strong background in software/AI development and at least 2+ years of experience in transformer-based NLP models.

Key Responsibilities:

  • Work with transformer models (GPT, BERT, T5, RoBERTa, etc.) across various NLP tasks, including text generation, summarization, classification, and translation.
  • Fine-tune pre-trained models on domain-specific datasets to optimize for summarization, text generation, question answering, and related tasks.
  • Design, test, and iterate on contextually relevant prompts to guide model outputs for desired performance.
  • Implement and refine instruction-based prompting strategies to achieve contextually accurate results.
  • Apply zero-shot, few-shot, and many-shot learning methods to maximize model performance without extensive retraining.
  • Leverage Chain-of-Thought (CoT) prompting for structured, step-by-step reasoning in complex tasks.
  • Evaluate model performance using BLEU, ROUGE, and other relevant metrics; identify opportunities for improvement.
  • Deploy trained and fine-tuned models into production environments, integrating with real-time systems and pipelines.
  • Identify, monitor, and mitigate issues related to bias, hallucinations, and knowledge cutoffs in LLMs.

Must-Have Skills:

  • 7+ years of overall experience in software/AI development with at least 2+ years in transformer-based NLP models.
  • 4+ years of hands-on expertise with transformer architectures (GPT, BERT, T5, RoBERTa, etc.).
  • Strong understanding of attention mechanisms, self-attention layers, tokenization, embeddings, and context windows.
  • Proven experience in fine-tuning pre-trained models for NLP tasks (summarization, classification, text generation, translation, Q&A).
  • Expertise in prompt engineering, including zero-shot, few-shot, many-shot learning, and prompt template creation.
  • Experience with instruction-based prompting and Chain-of-Thought prompting for reasoning tasks.
  • Proficiency in Python and NLP libraries/frameworks such as Hugging Face Transformers, SpaCy, NLTK, PyTorch, TensorFlow.
  • Strong knowledge of model evaluation metrics (BLEU, ROUGE, perplexity, etc.).
  • Experience in deploying models into production environments.
  • Awareness of bias, hallucinations, and limitations in LLM outputs.

Good to Have:

  • Experience with LLM observability tools and monitoring pipelines.
  • Exposure to cloud platforms (AWS, GCP, Azure) for scalable model deployment.
  • Knowledge of MLOps practices for model lifecycle management.

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