• Champion the developer experience by building the internal platform and tooling that every AI engineer at our company trusts and relies on. • Craft intuitive dashboards, user-friendly CLI tools, clean APIs, and elegant automation. • Develop intuitive and accessible internal platform interfaces—such as dashboards, model registries, and experiment trackers—using React and Next.js. • Design and support reliable backend services and APIs in Python. • Create and refine thoughtful automation for model deployment, rollbacks, and scaling workflows using scripts, APIs, and Infrastructure as Code (IaC). • Weave monitoring and observability tools (such as Grafana, Prometheus, DataDog, and LangSmith) directly into the platform. • Write comprehensive testing, evaluation, and validation logic for machine learning pipeline components.

• Design, fine-tune, and optimize advanced machine learning models for Arabic voice applications. • Work across the full development lifecycle, from data pipeline construction and model experimentation to inference optimization and production deployment. • Benchmark and evaluate TTS and ASR models using Arabic-specific test sets, measuring metrics such as Word Error Rate (WER), naturalness, and dialect coverage. • Fine-tune generative models for voice cloning, zero-shot speaker adaptation, and speech synthesis. • Build and maintain Arabic-focused data pipelines, including: Audio collection and preprocessing Diacritization (Tashkil) Data cleaning and augmentation. • Optimize model inference for production environments using: Quantization KV-cache tuning Streaming inference techniques. • Integrate and evaluate complete speech-to-speech conversational pipelines. • Conduct experiments based on recent research papers and convert findings into production-ready solutions. • Collaborate with engineering and product teams to deploy robust and scalable speech systems.

• Design ranking and retrieval models for main page, related content, and search • Build real-time recommendation systems for videos, shorts and infinite scroll timelines • Develop end-to-end recommendation pipelines, contributing to backend • Explore algorithms for Shorts generation

• Experience daily immersion in automotive industry data • Collaborate with data science and engineering teams to build and maintain model training and forecasting/prediction ETL pipelines with appropriate data mappings, anomaly detection, feature engineering, and data imputation strategies • Deploy models and ETL pipelines in a reusable framework to generate predictions or forecasts for use in existing and net-new products • Lead the creation of model and data drift monitoring pipelines and reporting • Communications of technical topics to both lay and technical business stakeholders, product, and senior data science leadership while requiring minimal feedback for communication documents and presentations • Leads quarterly planning for major ML deployment projects with minimal supervision