Job Description: 
Founded by Michael Lahyani in 2005 as a magazine (Al Bab World), Property Finder is now a single technology platform and brand across multiple countries in the MENA region. We provide the most cutting-edge tools and the best-in-class user experience for home seekers, real estate brokers, and developers. Our most recent valuation solidifies our status as one of the emerging unicorns in the Middle East, affirming a growth-oriented identity. Over the years, we have expanded our operations to Bahrain, Egypt, Qatar, and Saudi Arabia, and we have acquired a strategic shareholding in Hepsiemlak, the leading property portal in Turkey. With more than 600 committed employees spread across six regional offices, we facilitate over 14 million monthly visits across our platforms, solidifying our position as a regional powerhouse in the proptech space.
Our purpose as the area's first home-search platform is to inspire and encourage individuals to live the lives they deserve.
Summaeary:
In order to drive personalization, automation, and innovation across our platforms, we are seeking a qualified professional with experience in both Machine Learning Engineering (MLE Level II) and Data Science (Level II) to join our AI & Data Science team at Property Finder. The ideal candidate will have a solid foundation in machine learning, hands-on experience with transformer architectures, and the capacity to work across teams to deliver impactful AI-driven solutions. Join a forward-thinking team at the forefront of innovation, working on cutting-edge projects that employ GenAI and Large Language Models (LLMs) to revolutionize the real estate experience.Participate in a dynamic, cooperative atmosphere that emphasizes cooperation, technical proficiency, and ongoing learning. You will have the chance to develop professionally and have a significant influence in a field that is always changing thanks to exposure to cutting-edge AI technology and demanding projects.
Principal Duties:
. thorough comprehension and practical expertise in neural network designs and deep learning
. Create, optimize, and implement generative models and Large Language Models (LLMs) based on business requirements.
. Use transformer-based architectures, such GPT, BERT, T5, or comparable frameworks, to create applications.
. Use generative AI to implement use cases in process automation, content production, and customization.
. Improve the performance of LLM for inference in large-scale or real-time production settings.
. Investigate and test potential enhancements for GenAI and LLM applications.
. Create and manage scalable machine learning pipelines to effectively implement generative models and LLMs.
. Create processes for optimizing and supporting transformer models in manufacturing.
. Use MLOps technologies, such as Docker, MLflow, and Kubernetes, to automate the deployment process.
. To enable transformer-based models, streamline feature engineering procedures and data pipelines.
. Create and use machine learning models for customization and predictive analysis.
. Work together with cross-functional teams to support company initiatives and produce actionable insights.
. Perform sophisticated statistical analysis, feature engineering, and data wrangling.
. Create and assess experiments (such as A/B testing) to confirm the performance of the model.
. To match model development with business objectives, collaborate with the GenAI team.
. Work closely with MLE and Data Science teams to ensure seamless integration of LLMs and generative solutions into production workflows.
. Work along with the Futurism team to investigate innovative AI uses and LLM prospects.
The Person
Desired Qualifications
. The ideal candidate will have a bachelor's or master's degree in computer science, machine learning, data science, or a similar discipline; 
. two or more years of experience in machine learning engineering and data science roles, including two or more years of hands-on experience with transformers, LLMs, and generative models; 
. proficiency with Hugging Face Transformers, OpenAI APIs, and LangChain; 
. knowledge of attention mechanisms and sequence-to-sequence modeling; strong familiarity with ML pipelines and MLOps tools (e.g., Kubernetes, Docker, MLflow); 
. advanced SQL and Python programming skills; familiarity with cloud platforms (AWS, GCP, Azure) for scalable deployments; intermediate experience with supervised and unsupervised learning algorithms; 
. proficiency with data wrangling and feature engineering.
. understanding of hypothesis testing and statistical analysis.
. strong ability to analyze and solve problems.
. Proficiency in communication is essential for working with cross-functional teams.
. the capacity to adjust to a dynamic, fast-paced workplace.
Our commitment to talent is to provide our employees, known as creators, with numerous opportunities to contribute to a rapidly expanding and talent-focused organization. Ultimately, we want to make sure that our employees find their time at Property Finder to be a fulfilling experience where personal growth results from the company's expansion.
Property Finder Principles: 
. Move quickly and take action; 
. Data is superior to opinions; 
. Don't conflate motion with development; 
. Failure is success if we learn from it; 
. People are more important than pixels