Engineer AI

3 weeks ago

Dubai, Dubai, United Arab Emirates Michael page Full time
Lead the development of AI products leveraging RAG, LLM, or NLP. Create scalable, real-world AI solutions that drive business value.

Collaborate with cross-functional teams, including data scientists, product managers, and software engineers, to create and scale AI solutions.

Manage the end-to-end lifecycle of AI products, from initial ideation and prototyping to production deployment and post-release improvements.

Develop models and algorithms for a variety of applications, including text generation, semantic search, information retrieval, and more.

Optimise models for performance, scalability, and robustness in real-world environments.

Ensure that AI solutions are aligned with business goals, delivering value and enhancing customer experiences.

Stay up-to-date with the latest advancements in AI, machine learning, and NLP to continuously improve the company's AI capabilities.

Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field.

Proven experience with RAG, LLMs, and/or NLP technologies.

Hands-on experience in building and deploying AI models from the ground up, taking projects from concept to production.

Strong programming skills in Python, with experience using AI/ML libraries such as TensorFlow, PyTorch, Hugging Face, or similar frameworks.

Experience with cloud platforms (preferably Azure) for AI model development and deployment.

Designing and building AI models using machine learning algorithms, deep learning techniques, and natural language processing.

Collecting, cleaning, and preprocessing large datasets to ensure data quality and suitability for training AI models.

Implementing and optimising algorithms for specific applications, such as image recognition, recommendation systems, or predictive analytics.

Evaluating and fine-tuning AI models for accuracy, efficiency, and scalability, using metrics such as precision, recall, and F1 score.

Working with cross-functional teams, including data scientists, software engineers, and business stakeholders, to integrate AI solutions into existing systems.

Staying updated on the latest advancements in AI and machine learning technologies, and applying new techniques to improve models.

Managing the deployment of AI models into production environments, ensuring they operate effectively and efficiently.

Continuously monitoring AI systems for performance issues and updating models as necessary to adapt to changing data or business needs.

Creating and maintaining documentation for AI processes, models, and code to ensure clarity and reproducibility.

Ensuring that AI solutions comply with ethical standards and regulatory requirements, particularly regarding data privacy and bias.

Programming proficiency: Strong coding skills in languages such as Python, R, or Java, along with experience in AI frameworks (e.g., TensorFlow, PyTorch, Keras).

Solid understanding of mathematical concepts, statistics, and algorithms used in machine learning and data analysis.

Deep knowledge of machine learning techniques, including supervised and unsupervised learning, reinforcement learning, and deep learning.

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