Artificial Intelligence Engineer

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About the Company

We are a fast-growing technology firm focused on building next-generation AI solutions that drive automation, intelligence, and decision-making across industries. Our team combines expertise in machine learning, natural language processing, and generative AI to solve complex business challenges using data-driven innovation.

About the Role

AI Engineer

Key Responsibilities

• Design, develop, and deploy

  AI and ML models

  to solve business and product challenges.
• Build and optimize

  NLP pipelines

  for tasks such as text classification, entity extraction, and sentiment analysis.
• Implement

  Retrieval-Augmented Generation (RAG)

  architectures using LLMs and vector databases.
• Fine-tune pre-trained

  Large Language Models (LLMs)

  for domain-specific applications.
• Develop and integrate AI solutions into production systems using Python APIs or web frameworks.
  
• Collaborate with data engineers, backend developers, and product teams to ensure scalable AI deployment.
  
• Research and experiment with emerging AI/ML tools, frameworks, and architectures to improve model performance.
  
• Evaluate and monitor AI model performance using key metrics (accuracy, F1-score, perplexity, etc.).
  

Required Skills

• 3-8 years

  of hands-on experience in

  AI/ML model development and deployment

  .
• Strong programming skills in

  Python

  and familiarity with

  machine learning frameworks

  like

  TensorFlow

  ,

  PyTorch

  , or

  Hugging Face Transformers

  .
• Experience with

  Natural Language Processing (NLP)

  tokenization, embeddings, and transformer-based architectures (BERT, GPT, etc.).
• Practical knowledge of

  Retrieval-Augmented Generation (RAG)

  using tools like

  LangChain

  ,

  LlamaIndex

  , or

  FAISS

  .
• Proficiency in

  vector databases

  (Pinecone, ChromaDB, Weaviate, Milvus, etc.).
• Strong understanding of

  data preprocessing

  ,

  feature engineering

  , and

  model evaluation

  .
• Experience in

  cloud deployment

  (AWS, GCP, or Azure) and

  containerization

  (Docker).
• Experience working with

  LLM APIs

  (OpenAI, Anthropic, Mistral, etc.).
• Familiarity with

  knowledge graph construction

  or

  semantic search systems

  .
• Understanding of

  data pipelines

  and

  ETL workflows

  .
• Knowledge of

  API development

  or

  backend integration

  with Flask/FastAPI.