Machine Learning Engineer

About GlobalDrum

GlobalDrum is revolutionizing the media industry by enabling brands to own, comprehend, and monetize their social audiences live using behavioral data. Operating a next-gen B2B2C Platform as a Service on a global cloud infrastructure with scalable, event-driven AI architecture, the company is transforming a digital ad market projected at $276Bn by 2025. Headquartered across London, Dubai, and New York, GlobalDrum aims to reshape how major brands evolve in the digital space.

Role Overview

As the inaugural Machine Learning Engineer, you will embed data science and applied machine learning centrally within the AI-native, multi-tenant platform. Collaborating closely with the Director of Engineering and product teams, your mission is to develop models that drive recommendations, audience insights, and revenue decisions. This unique position allows you to establish the ML function from scratch, including choosing technologies, setting standards, and constructing production models that will underpin the engineering organization.

Key Responsibilities

• Lead the end-to-end design, development, and iteration of recommender systems that identify content and audience opportunities for media partners.
• Develop the foundational ML infrastructure, including pipelines, feature stores, experimentation frameworks, and model-serving capabilities, currently non-existent in the platform.
• Collaborate with the engineering team to implement real-time, event-driven data pipelines for training models and enabling low-latency inference.
• Design offline and online evaluation methodologies employing A/B testing, holdout datasets, and ranking metrics to measure model effects on engagement and revenue.
• Define and enforce best practices in model development, version control, reproducibility, monitoring, and ethical data usage.
• Stay actively involved in writing production-ready ML code, utilizing modern AI coding assistants and agentic development workflows to accelerate progress initially as a solo contributor.
• Work cross-functionally with engineering and product stakeholders to translate business challenges into machine learning solutions.
• Shape the future ML team roadmap and recruitment strategy as the first hire in this function.

Required Qualifications and Expertise

• Demonstrated experience designing and deploying recommender systems in production settings.
• Proficiency with graph learning approaches, including Graph Neural Networks.
• Strong grasp of network science principles.
• Experience managing model training on extensive real-world datasets, addressing data sparsity and imbalanced engagement patterns.
• Comprehensive understanding of the complete ML lifecycle: feature engineering, training, evaluation, deployment, and monitoring.
• Fluency with contemporary ML frameworks like PyTorch or TensorFlow and familiarity with standard MLOps methodologies.
• Experience leveraging AI coding tools and agentic workflows to boost development efficiency.
• Proven ability to thrive in a dynamic, early-stage startup environment.

Additional Desirable Experience

• Background in media or news technology industries.
• Familiarity with advertising technology including ad networks, ad serving, and audience segmentation.

Preferred Skills

• In-depth domain knowledge in SaaS/PaaS, marketing technology, or advertising technology sectors.
• Expertise in building models that directly influence platform revenue metrics.
• Experience with recommendation systems utilizing large language models (LLMs) and visual language models (VLMs).
• Comfort with being the sole ML expert initially and communicating complex ML concepts to non-expert engineering and product team members.

Why Work With Us?

• An opportunity to pioneer an innovative AI platform from its inception.
• Competitive compensation including equity package.
• Flexible work environment based in Dubai.