Generative AI Engineer

Carbon Technologies Inc. is hiring a Generative AI Engineer in Toronto, ON. The role requires a PhD and expertise in large language models, focusing on integration, fine-tuning, and performance optimization for voice-activated applications. Key responsibilities include model enhancement, system design, testing, and collaboration with diverse teams. Candidates should have experience with NLP, deep learning frameworks, and AI systems. The position involves creating a 3B parameter reasoning model for robotic products.
Job Description:

We are seeking an experienced LLM Engineer with robust expertise in large language model development, integration, fine-tuning, and augmentation. The ideal candidate will excel at enhancing pre-trained models, ensuring seamless integration into voice-activated applications, and delivering precise and reliable performance. A PhD is required, as deep understanding of model architectures and inner workings is crucial for our advanced projects.

We are intending to create our own 3B parameter reasoning model to drive our Robot products. it will be a truly challenging task but it will be incredibly fun if this is something you enjoy.

Key Responsibilities:

LLM Integration & Modeling:
• Develop and optimize integration strategies for pre-trained large language models into voice and conversational applications.
• Enhance model performance through fine-tuning and custom augmentation techniques while ensuring compliance with safety and quality standards.
• Collaborate closely with AI research teams to implement model improvements and incorporate advanced language understanding capabilities.

System Design & Customization:
• Adapt and extend pre-trained models with additional layers and modules to meet specific application requirements.
• Analyze and refine model architectures to address complex interaction scenarios and ensure optimal performance under varying operational conditions.
• Integrate cutting-edge techniques to address challenges in voice recognition, natural language understanding, and contextual response generation.

Testing, Analysis & Optimization:
• Lead rigorous testing protocols to evaluate model performance, robustness, and adherence to defined tolerances.
• Work with cross-functional teams to analyze outputs, identify areas for improvement, and implement iterative refinements.
• Oversee debugging and performance evaluation initiatives, ensuring that the final product meets the highest standards of reliability and user satisfaction.

Technical Documentation & Collaboration:
• Prepare comprehensive technical documentation, including detailed descriptions of model modifications, configuration settings, and integration strategies.
• Maintain clear revision control and documentation standards to support continuous improvement and knowledge sharing.
• Collaborate with multidisciplinary teams, including software engineers, data scientists, and UX designers, to ensure smooth implementation and operational excellence.

Required Qualifications:
• PhD in Computer Science, or a related field with a focus on artificial intelligence and deep learning.
• Proven experience with large language models and transformer architectures, including hands-on experience in model fine-tuning and augmentation.
• Strong understanding of natural language processing (NLP) principles, deep learning frameworks (e.g., PyTorch, TensorFlow), and system integration techniques.
• Demonstrated ability to design, develop, and optimize complex AI systems with voice-activated or conversational interfaces.
• Excellent analytical skills, attention to detail, and a commitment to producing high-quality, reliable solutions.
• Effective communication skills and a collaborative mindset to work within interdisciplinary teams.

Preferred Qualifications:
• Prior experience with cloud-based AI services and distributed model training.
• Knowledge of AI ethics, safety standards, and regulatory considerations related to voice and conversational systems.
• Background in voice recognition technologies and integration of multi-modal interaction systems.
• Experience in agile or startup environments, with a track record of managing fast-paced, innovative projects.

This role is ideal for a forward-thinking engineer ready to drive innovation in advanced language model applications and voice-enabled technologies.