Machine Learning Specialist

Lead Data Scientist - Generative AI 

We are seeking a Lead Data Scientist to architect and build next-generation voice-enabled virtual assistants powered by large language models. This role will focus on creating seamless, natural conversational experiences that combine advanced LLMs with state-of-the-art voice AI technologies.

Key Responsibilities

• Lead the design and development of intelligent virtual assistants that integrate LLMs with real-time voice interaction capabilities
  
• Architect end-to-end conversational AI pipelines, including speech recognition, natural language understanding, LLM reasoning, response generation, and text-to-speech synthesis
  
• Optimize LLM performance for conversational contexts, including prompt engineering, fine-tuning, and context management for multi-turn dialogues
  
• Design and implement low-latency inference systems to enable responsive, human-like voice conversations
  
• Build evaluation frameworks to measure conversation quality, coherence, accuracy, and user satisfaction
  
• Integrate multi-modal capabilities allowing the assistant to process and respond to both voice and text inputs seamlessly
  

Requirements

Technical Focus Areas

• LLM Integration: Adapting large language models (GPT, Claude, Llama, etc.) for conversational contexts and virtual assistant use cases
  
• Conversational AI: Dialogue management, context tracking, memory systems, and multi-turn conversation optimization
  
• Real-time Systems: Low-latency streaming architectures for natural voice interactions with minimal delay
  
• Personalization: Building adaptive systems that learn user preferences and communication styles
  

Required Qualifications

• PhD or Master's degree in Computer Science, AI, NLP, or related field with 4+ years of experience,
  
• Extensive experience working with large language models (GPT-4, Claude, Gemini, LLaMA, etc.) and prompt engineering
  
• Deep understanding of conversational AI architecture, including dialogue systems and natural language understanding
  
• Strong knowledge of transformer architectures and experience fine-tuning LLMs for specific domains
  
• Proficiency with modern ML frameworks (PyTorch, TensorFlow) and LLM APIs (OpenAI, Anthropic, etc.)
  
• Experience optimizing models for production, including latency reduction and cost optimization
  
• Proficient in English (mandatory).