مهندس الذكاء الاصطناعي

Roles and responsibilities

As the AI Lead Engineer, you will be responsible for leading the design and implementation of cutting-edge AI solutions, including the use of Large Language Models (LLMs), multi-modality, and other innovative AI technologies. You will oversee the creation of AI architectures that drive content personalization, automation, and predictive analytics across text (NLP), image, audio, and video data. Collaborating with cross-functional teams, you will ensure the successful integration of AI into the company’s platforms, providing innovative solutions for content creation, recommendation, and media analysis.

Key Responsibilities

• Lead the design, development, and implementation of AI and machine learning models, including the use of LLMs, multi-modality models, and other innovative AI technologies.
• Develop and optimize AI-driven systems for content recommendation, personalization, and automation, leveraging deep learning techniques across text, image, audio, and video data.
• Collaborate with engineering, product, and data science teams to integrate AI solutions into backend systems and customer-facing platforms.
• Utilize LLMs, computer vision, speech recognition, and generative AI models to solve complex business problems and enhance user experiences across multimedia formats.
• Build scalable AI pipelines, ensuring seamless deployment and maintenance in cloud environments.
• Implement data preprocessing, feature engineering, and model training workflows to support AI/ML initiatives in various media formats (text, images, audio, and video).
• Monitor AI models to ensure accuracy, relevancy, and fairness, retraining or refining models as needed.
• Stay up-to-date with the latest advancements in AI technologies, including CNNs, RNNs, GANs, Transformers, Diffusion Models, and Rectified Flow, and apply them to real-world use cases.
• Establish best practices for AI model development, versioning, and MLOps (Machine Learning Operations) across the team.
• Provide technical leadership and mentorship to the AI engineering team, fostering innovation and delivering high-quality AI solutions.
• Work closely with cloud architects and DevOps teams to ensure efficient AI model deployment and performance monitoring.
• Maintain comprehensive documentation for AI models, processes, and architectures, ensuring transparency and collaboration across teams.

Desired candidate profile

Skills

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
• 10+ years of experience in AI, machine learning, or data science, with a focus on deploying LLMs and innovative AI models across text, image, audio, and video processing.
• Expertise in multi-modality AI models, integrating data from multiple sources (text, image, audio, video).
• Expertise in machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and natural language processing (NLP).
• Proven experience with LLMs, generative AI models, and advanced machine learning techniques for multimedia data.
• Strong experience with cloud platforms like AWS for AI model deployment and scaling.
• Proficiency in programming languages such as Python, R.
• Strong understanding of AI ethics, fairness, and bias mitigation in AI systems.
• Up-to-date knowledge of deep learning advancements like CNNs, RNNs, GANs, Transformers, Diffusion Models, and Rectified Flow, particularly in multimedia applications.
• Proven experience with MLOps, including AI model versioning, CI/CD pipelines, and performance monitoring.
• Excellent problem-solving and analytical skills, with the ability to design and implement complex AI solutions.
• Strong leadership and team collaboration skills, with experience mentoring AI engineers and leading cross-functional initiatives.
• High proficiency in English, both written and verbal, is essential.