AIML Lead

About us:
University Living is a global student housing marketplace that helps international students find the best place to stay near university campuses around the world. Currently, our platform offers 2Mn beds in 65K + properties across 512+ international education hubs in the UK, Ireland, USA, Canada, Europe, Australia, New Zealand, Singapore & UAE. Students can consult a 24/7 support team of accommodation experts to discover, compare and book value-for-money accommodation based on their budget, desired location, and other personal preferences.

As the AI & ML Lead, you will spearhead the development of our conversational AI system. You will define the technical strategy, lead model design and implementation, and work on large language models (LLMs) to fine-tune, deploy, and optimize human-like conversational agents. This role involves hands-on development, collaboration with cross-functional teams, and leveraging tools such as OpenAI and cloud systems like AWS for scalable AI deployments.

Key Responsibilities:
• Lead the end-to-end development of AI models for a conversational human-like calling agent.
• Define and implement ML and LLM model architectures tailored to our requirements.
• Fine-tune pre-trained models (e.g., BERT, GPT, OpenAI models) and integrate Retrieval-Augmented
• Generation (RAG) techniques to enhance response accuracy and relevance.
• Have good understanding of integrating voice APIs such as Twilio, Vonage etc.
• Collaborate on data preparation, feature engineering, and model training workflows.
• Deploy models on cloud infrastructure (e.g., AWS, GCP, Azure) and continuously optimize for performance, accuracy, and scalability.
• Leverage OpenAI and similar tools for model innovation, experimentation, and fine-tuning.
• Stay updated on the latest trends in NLP, ML, and AI to integrate new advancements.
• Mentor junior team members and guide research into new AI technologies.

Required Skills & Qualifications:
• 6+ years of hands-on experience in AI/ML, with a strong focus on natural language processing (NLP), large language models (LLMs), and tools like OpenAI.

• Proven expertise in designing, fine-tuning, and deploying machine learning models (preferably
  conversational AI).
  • Experience with Retrieval-Augmented Generation (RAG) techniques for improving model responses.
  • Strong coding skills in Python, TensorFlow, PyTorch, or similar frameworks.
  • Experience with cloud-based AI solutions (e.g., AWS, GCP, Azure) for deploying and scaling models.
  • Familiarity with speech recognition, dialogue systems, and human-computer interaction technologies.
  • Solid understanding of MLOps practices, including model versioning, monitoring, and CI/CD pipelines.
  • Exceptional problem-solving skills and the ability to lead technical initiatives.
  
• Nice to Have:
  • Experience building conversational agents or voice-based AI systems.
  • Exposure to OpenAI models and tools, with experience in utilizing GPT-based models.
  • Understanding of data privacy regulations and ethical AI considerations.