AI Engineer

2 weeks ago

Lahore, Punjab, Pakistan Big Entities Full time $90,000 - $120,000 per year

Job Summary:

We are seeking an experienced 
AI/ML Engineer

with a minimum of 
4 years of hands-on experience

in 
Natural Language Processing (NLP)

and 
LLM (Large Language Model)

-based solutions. The ideal candidate should have a strong background in 
Retrieval-Augmented Generation (RAG)

, 
vector database design

, 
chunking strategies

, and 
chatbot development

, along with proven expertise in 
fine-tuning and integrating LLMs

for real-world applications.

Key Responsibilities:

·      Design and develop 
NLP pipelines
 to process and extract insights from unstructured data.

·      Build and optimize 
RAG (Retrieval-Augmented Generation)
 workflows for LLM-based systems.

·      Implement 
chunking strategies
 to improve information retrieval and response accuracy.

·      Work with 
vector databases
 (e.g., Pinecone, Weaviate, FAISS) to store and retrieve embeddings efficiently.

·      Develop 
conversational AI/chatbot
 solutions using modern frameworks and APIs.

·      Fine-tune, integrate, and deploy 
LLMs (Open-source or proprietary)
 based on application needs.

·      Collaborate with product and engineering teams to translate business requirements into intelligent AI-driven features.

·      Conduct experiments, evaluate model performance, and optimize pipelines for scalability and accuracy.

Required Skills & Qualifications:

· years of experience in 
AI/ML Engineering
, with a strong focus on 
NLP
.

·      Proven experience with 
RAG frameworks
, 
LLM fine-tuning
, and 
prompt engineering
.

·      Hands-on experience with 
vector databases
 such as 
FAISS, Pinecone, Chroma, Weaviate
, etc.

·      Strong understanding of 
embedding models
, 
tokenization
, and 
text chunking techniques
.

·      Experience in building 
chatbots
 and integrating with LLMs (OpenAI, Cohere, HuggingFace, etc.).

·      Proficiency in 
Python
 and libraries like 
LangChain, Transformers, PyTorch, or TensorFlow
.

·      Experience with deploying models using 
APIs
, 
microservices
, or containerized solutions.

  • Familiarity with MCP (Model Context Protocol), tool calling, and preferably agent-based frameworks (Agent Boot or similar) for building autonomous AI workflows.

Nice to Have:

·      Experience with 
multi-modal models
 (e.g., text + images).

·      Knowledge of 
data privacy
 and 
security best practices
 in AI systems.

·      Exposure to 
cloud services
 specially Azure for AI/ML workloads.

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