Technical Lead, IT​/Tech, AI Engineer

We are seeking a talented and motivated AI Engineer with expertise in Large Language Models (LLMs), Natural Language Processing (NLP), and Speech-to-Text technologies.

As part of our dynamic team, you will design, develop, and deploy next-generation AI solutions that enhance our products and services through intelligent automation, language understanding, and seamless communication systems.

• LLM Development & Integration

  Fine-tune and deploy Large Language Models for chatbots, content generation, and virtual assistants. Evaluate and optimize model performance in real-world use cases. Integrate LLMs into production environments ensuring scalability and reliability.

• NLP System Design

  Design and implement NLP algorithms for text classification, sentiment analysis, entity recognition, and summarization. Handle large text datasets for model training and validation. Collaborate with cross-functional teams to address language-related challenges.

• Speech-to-Text Implementation

  Develop and optimize speech-to-text (ASR) pipelines for multiple languages and dialects. Integrate speech recognition systems with NLP and LLM modules for end-to-end conversational experiences. Stay updated with advancements in Automatic Speech Recognition (ASR) technologies.

• Performance Optimization

  Improve AI model efficiency for real-time performance and scalability. Identify and mitigate biases to ensure model accuracy, fairness, and robustness.

• Research & Innovation

  Stay current with cutting-edge research in LLMs, NLP, and Speech AI. Experiment with new architectures and techniques to drive innovation.

• Documentation & Collaboration

  Maintain detailed documentation of models, datasets, and workflows. Collaborate with product managers, software engineers, and other stakeholders to deliver production-grade AI solutions.

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related fields.
• Proven experience in LLM development (e.g., OpenAI GPT, Claude, or similar frameworks).
• Strong knowledge of NLP libraries (e.g., Hugging Face, spaCy, NLTK).
• Hands-on experience with speech-to-text tools (e.g., Whisper, Google Speech API, Deep Speech).
• Proficiency in Python and frameworks like Tensor Flow or PyTorch.
• Excellent analytical, problem-solving, and communication skills.