Senior AI/ML Engineer

2 days ago

Bengaluru, Karnataka, India beBeeMachine Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

Job Description:

The Position:

Seeking a seasoned data scientist with expertise in deep learning and traditional machine learning to drive high-impact solutions aligned with our AI product strategy.

This role is perfect for someone who excels in fast-paced environments and focuses on delivering sophisticated AI/ML projects from inception to deployment.

  • Develop advanced NLP models and algorithms for entity extraction and document processing.
  • Fine-tune and optimize LLMs and Generative AI models.
  • Build and deploy solutions using Retrieval-Augmented Generation (RAG), Langchain, Langgraph, and LLM Agents to enhance model responses and data retrieval processes.
  • Evaluate and ensure efficient serving, maintenance, and optimization of models.
  • Work with Vector Databases (e.g., Milvus, Chroma, Pinecone, etc.) for scalable AI solutions.
  • Provide mentorship and technical guidance to team members.

Requirements:

Required Skills and Qualifications
  • Strong understanding of data science fundamentals and best practices.
  • Proven expertise in Python, including development of scalable ML pipelines.
  • Proven experience in NLP and transformers, and Generative AI.
  • Hands-on experience with LLMs, their fine-tuning, and frameworks such as Langchain, Langgraph, and LLM Agents.
  • Expertise in model serving and optimization.
  • Proficiency in Python and extensive experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
  • Experience with cloud services (AWS, GCP, Azure).
  • Familiarity with ML platforms (ex., Azure-ML, Amazon SageMaker, etc.) for deploying and managing LLM-based applications.
  • Knowledge of MLOps practices and scalable AI/ML architecture.
  • Experience with document AI and large-scale data processing.
  • Bachelor's or Master's degree in Computer Science, Data Science, or related fields.
  • 6+ years of experience with a strong portfolio in Deep Learning and Traditional Machine Learning.

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