AI/ML Engineer

2 days ago

Kottayam, Kerala, India beBeeGenerative Full time ₹ 1,80,00,000 - ₹ 2,20,00,000

Job Title: AI/ML Model Architect - Generative AI

Job Description:

We are seeking an experienced and highly skilled AI/ML Model Architect to design, develop, and deploy scalable ML solutions using large language models (LLMs) and retrieval-augmented generation (RAG). The ideal candidate will have a strong background in machine learning, experience with LLMs, and the ability to work collaboratively with data engineers, product managers, and other stakeholders.

The successful candidate will be responsible for designing and developing ML solutions that can solve complex business problems and enhance product capabilities. This includes implementing and optimizing prompt engineering, embeddings, vector databases, and retrieval mechanisms, as well as developing APIs and services to integrate AI solutions into production systems.

Key Responsibilities:

  • Design and develop scalable ML solutions using LLMs and RAG architecture.
  • Implement and optimize prompt engineering, embeddings, vector databases, and retrieval mechanisms.
  • Develop APIs and services to integrate AI solutions into production systems.
  • Collaborate with data engineers, product managers, and other stakeholders to define technical requirements.
  • Continuously evaluate and improve model performance and accuracy.
  • Stay updated with the latest research and developments in GenAI, NLP, and ML.
  • Contribute to technical documentation, code reviews, and best practices.
  • Ensure all AI solutions comply with ethical and data privacy standards.

Required Skills and Qualifications:

Essential Qualifications:

  • Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
  • Strong programming skills in Python, including use of libraries like TensorFlow, PyTorch, Hugging Face Transformers, LangChain, etc.
  • Experience with LLMs (GPT, LLaMA, Claude, etc.) and RAG frameworks.
  • Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate).
  • Solid understanding of NLP, embeddings, tokenization, and attention mechanisms.
  • Familiarity with APIs, RESTful services, and cloud deployment (AWS/GCP/Azure).
  • Strong foundation in data structures, algorithms, and ML workflows.

Preferred Qualifications:

  • Ph.D. in a relevant field.
  • Experience deploying LLMs in production environments.
  • Contributions to open-source GenAI projects or research publications.
  • Knowledge of MLOps and CI/CD for ML pipelines.
  • Experience with Kubernetes, Docker, or other containerization tools.

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