Software Engineer - LLM

Description

About the Role :

Key Responsibilities

• Develop, fine-tune, and deploy Large Language Models (LLMs) for applications such as chatbots, summarization, recommendation systems, and search.
• Work with transformer-based architectures (e.g., GPT, BERT, T5, LLaMA) to implement and optimize LLMs for various tasks.
• Design and implement data pipelines for preprocessing, cleaning, and augmenting large-scale textual datasets.
• Optimize model performance for latency, throughput, and memory efficiency for production deployment.
• Collaborate with ML researchers to implement novel algorithms and improve model accuracy, reasoning, and generalization.
• Integrate LLMs into applications via APIs, microservices, and cloud-based platforms.
• Participate in code reviews, testing, and deployment pipelines to ensure high-quality, maintainable, and scalable software.
• Stay updated with the latest advancements in LLMs, NLP, and AI research and apply relevant techniques to projects.
  

Technical Skills

• Strong programming experience in Python, with proficiency in PyTorch, TensorFlow, or JAX.
• Hands-on experience with transformer architectures and LLM frameworks such as Hugging Face Transformers, OpenAI API, or DeepSpeed.
• Experience with fine-tuning, prompt engineering, and model evaluation techniques.
• Knowledge of tokenization, embeddings, attention mechanisms, and sequence modeling.
• Experience in deploying models using cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).
• Familiarity with data processing frameworks such as Pandas, NumPy, PySpark, or Dask.
• Experience in training large models on GPU/TPU infrastructure and optimizing model inference.
• Understanding of MLOps practices, including CI/CD pipelines for AI models