AI/ML Engineer Speech, RAG & Fine-Tuning

Job Title: AI/ML Engineer Speech, RAG & Fine-Tuning

Location: Bahria Town, Phase 7, Rawalpindi

Employment Type: Full-time,Onsite (10AM - 7PM)

Job Description:

We are seeking a highly skilled AI/ML Engineer with expertise in speech-to-speech pipelines, open-source models, and LLM fine-tuning . The ideal candidate will work on designing, developing, and deploying cutting-edge speech and language AI solutions , integrating open-source frameworks with advanced fine-tuning methods to deliver production-ready systems.

Key Responsibilities:

• Design and implement speech-to-speech pipelines using open-source models (Whisper, Wav2Vec, etc.).
• Develop and optimize speech-to-text (STT) and text-to-speech (TTS) systems leveraging Coqui or similar frameworks.
• Work with large language models (LLMs) such as LLaMA 2, LLaMA 3 for NLP applications.
• Apply LoRA and PEFT-based fine-tuning techniques to customize LLMs for domain-specific tasks.
• Build and optimize Retrieval-Augmented Generation (RAG)-based systems for knowledge-grounded responses.
• Develop and integrate agentic AI systems with reasoning and task automation capabilities.
• Collaborate with cross-functional teams (data engineers, product managers, software developers) to deliver scalable AI solutions.
• Monitor, evaluate, and optimize deployed AI models for accuracy, latency, and efficiency.
  
  
  

Requirements:

• Strong experience in AI/ML model development with open-source speech and language models.
• Hands-on experience with Whisper, Wav2Vec, Coqui TTS/STT frameworks.
• Proven track record with LLaMA 2, LLaMA 3 or similar LLMs.
• Proficiency in fine-tuning techniques: LoRA, PEFT, and parameter-efficient training.
• Experience in RAG-based systems for knowledge retrieval and contextual response generation.
• Familiarity with agentic AI frameworks for building task-oriented agents.
• Strong programming skills in Python, PyTorch, TensorFlow.
• Experience with Hugging Face, LangChain, and vector databases (FAISS, Pinecone, Weaviate, etc.).
• Knowledge of cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• Strong problem-solving skills and ability to optimize model performance.
  
  
  

Preferred Qualifications:

• Masters or PhD in Computer Science, AI/ML, Data Science, or related field.
• Publications or projects in speech AI, LLM fine-tuning, or agentic AI.
• Experience with distributed training and model deployment at scale.
  
  
  

What We Offer:

• Lunch provided by the company
• Medical Allowance
• Competitive compensation and growth opportunities.
• Opportunity to work with state-of-the-art open-source AI models.
• Collaborative environment with AI researchers and engineers.