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.

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.