Job Purpose
The purpose of this role is to design, develop, and deliver advanced machine learning and deep learning solutions with a strong focus on conversational AI, including chatbots and voice bots. The incumbent will apply extensive ML expertise—from classical methods to cutting-edge generative AI—to build high-impact solutions in Speech-to-Text, Text-to-Speech, OCR, and LLM-based conversational platforms. This includes developing and fine-tuning large language models (LLMs) for human-like chat and voice interactions, ensuring that solutions meet business objectives and customer experience goals. The role also involves leading agile projects, guiding a multidisciplinary team, and fostering a culture of innovation.
Report To Position Name
AI & ML Development
Demonstrate broad, in-depth knowledge of classical ML (e.g., regression, tree-based models, SVMs) and advanced deep learning (CNNs, RNNs, Transformers).
Develop end-to-end ML solutions, from data exploration and feature engineering to model deployment and monitoring.
Integrate and fine-tune generative AI models (e.g., GPT, Claude, …) and open-source LLMs for various applications, ensuring robust performance at scale.
Conversational AI: Chatbots & Voice Bots:
Design, develop, and deploy conversational AI solutions, including chatbots and voice bots powered by LLMs and speech technologies.
Implement Speech-to-Text (STT) and Text-to-Speech (TTS) solutions for voice-based user interfaces, ensuring natural, context-aware, human-like dialogues.
Conduct dialog management, intent classification, response generation, and speech analytics to enhance the user experience and optimize language models for accuracy and latency.
Speech Analytics Platform Management:
Manage the speech analytics platform, focusing on:
Oversee speech-to-text model fine-tuning, data annotation, model evaluation, and operational maintenance to improve transcription accuracy.
OCR & Document Processing
Implement OCR solutions (open-source or commercial) for large-scale document processing.
Integrate OCR outputs with backend systems and workflows where document-based queries or processing are required.
Generative AI & Retrieval-Augmented Generation (RAG)
Build RAG workflows using frameworks like LangChain to enhance conversational AI and document-based question-answering.
Combine classical ML with generative methods to deliver innovative customer-facing experiences.
Research & Innovation
Stay updated on ML/deep learning trends, focusing on conversational AI developments.
Propose proof-of-concepts (PoCs) to explore new ideas, demonstrating outside-the-box thinking to address business challenges.
Cultivate a culture of experimentation, enabling rapid prototyping and iteration on novel solutions.
Stakeholder Engagement
Collaborate with product owners, business analysts, and other stakeholders to translate requirements into conversational AI solutions that deliver measurable ROI.
Present complex AI concepts to non-technical audiences, emphasizing business value and customer experience impact.
Vendor Management:
Prepare RFPs and manage vendor relationships to procure new technologies or upgrades, ensuring compliance with SLAs and business objectives.
Manage the business relationships with the vendors starting from the cycle of RFPs and vendor selection until managing the platforms' operational issues to ensure maximum RIO on e& Egypt.
Support & Issue Resolution: Act as third-line support for escalated issues, providing swift resolutions and maintaining system reliability.
Team Leadership:
Manage the team members in terms of coaching, motivation, performance evaluation and training, ensuring efficient utilization of the resources' capacity, in order to meet the department's plans and reach the desired outcome.
Mentor and support team member, fostering a culture of technical excellence and continuous development.
Demonstration of team spirit and a proactive collaboration with cross functional projects.
QUALIFICATIONS_ESSENTIAL
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related discipline
QUALIFICATIONS_DESIRABLE
Technical Mastery: Expertise in Python and ML/DL frameworks (PyTorch, TensorFlow), plus proficiency with data libraries (NumPy, Pandas, scikit-learn).
- Broad ML Knowledge: Strong foundation in both classical ML and advanced DL architectures (CNNs, RNNs, Transformers).
- Conversational AI Focus: Deep knowledge of dialog management, NLP, intent classification, response generation, and LLM fine-tuning for chat/voice scenarios.
- Agile Mindset: Skilled in iterative development, rapid prototyping, and frequent stakeholder feedback.
- Leadership & Communication: Capable of guiding diverse teams, explaining technical concepts to non-technical audiences, and managing stakeholder expectations.
Innovation & Research: Passion for experimentation, exploring new frameworks, and evaluating emerging conversational AI technologies
- Customer & Business Focus: Committed to delivering AI solutions that enhance user experience and create measurable business value.
EXPERIENCE_ESSENTIAL
6+ years of hands-on experience in ML, deep learning, and data science roles.
Demonstrated success in generative AI (GPT, Claude, open-source LLMs) and fine-tuning large-scale models for conversational or chat-based applications.
Proven track record with chatbots, voice bots, speech technologies (speech-to-text, text-to-speech), and OCR Solutions.
Experience implementing RAG pipelines and knowledge of open-source libraries like LangChain.
Familiarity with cloud platforms (AWS, Azure) for model training, deployment, and monitoring at scale.
EXPERIENCE_DESIRABLE
CERTIFICATIONS_ESSENTIAL
n/a
