Qureos

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AI Engineer (Mid-Level)

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.

Key Responsibilities

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

Requirements

Qualifications

  • 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, DeepSpeech)
  • Proficiency in Python and frameworks like TensorFlow or PyTorch
  • Excellent analytical, problem-solving, and communication skills

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