مهندس الذكاء الاصطناعي

Roles and responsibilities

As the AI Lead Engineer, you will spearhead the design and implementation of advanced AI solutions, focusing on Large Language Models (LLMs), multi-modality systems, and other cutting-edge AI technologies. Your role will be pivotal in creating AI architectures that enhance content personalization, automation, and predictive analytics across various media formats, including text, images, audio, and video.

Key Responsibilities

• AI Model Development: Lead the design, development, and implementation of AI and machine learning models, particularly LLMs and multi-modality models, ensuring they address complex business challenges effectively.

• System Optimization: Develop and optimize AI-driven systems for content recommendation, personalization, and automation, utilizing deep learning techniques across diverse data types.

• Cross-Functional Collaboration: Work closely with engineering, product, and data science teams to seamlessly integrate AI solutions into both backend systems and customer-facing platforms.

• Advanced AI Techniques: Leverage LLMs, computer vision, speech recognition, and generative AI models to enhance user experiences and address business needs in multimedia contexts.

• Scalable Pipelines: Build and maintain scalable AI pipelines for efficient deployment and operations in cloud environments, ensuring high performance and reliability.

• Data Management: Implement robust data preprocessing, feature engineering, and model training workflows to support AI/ML initiatives across various media formats.

• Model Monitoring: Continuously monitor AI models for accuracy, relevancy, and fairness, making adjustments and retraining as necessary to maintain optimal performance.

• Research and Innovation: Stay abreast of the latest advancements in AI technologies, including CNNs, RNNs, GANs, Transformers, and Diffusion Models, applying these innovations to real-world use cases.

• Best Practices Establishment: Develop and enforce best practices for AI model development, versioning, and MLOps (Machine Learning Operations) to enhance team efficiency and output quality.

• Technical Leadership: Provide mentorship and technical leadership to the AI engineering team, fostering a culture of innovation and ensuring the delivery of high-quality AI solutions.

• Collaboration with DevOps: Partner with cloud architects and DevOps teams to ensure effective deployment of AI models and ongoing performance monitoring.

• Documentation and Transparency: Maintain comprehensive documentation for AI models, processes, and architectures to promote transparency and facilitate collaboration across teams.

Desired candidate profile

Skills and Qualifications

• Educational Background: Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.

• Extensive Experience: Over 10 years of experience in AI, machine learning, or data science, with a strong focus on deploying LLMs and innovative AI models across multimedia formats.

• Multi-Modality Expertise: Deep expertise in multi-modality AI models, integrating data from diverse sources (text, image, audio, video).

• Technical Proficiency: Proficient in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and natural language processing (NLP).

• Generative AI Experience: Proven track record with LLMs and advanced machine learning techniques tailored for multimedia data applications.

Join us in this exciting opportunity to lead the charge in innovative AI solutions, shaping the future of content creation and media analysis.