Principal ML Engineer - Personalisation

Beyond is a technology consultancy helping organizations thrive in a rapidly changing world.

We build, modernize, scale, and operationalize technology, creating Cloud and AI solutions to unlock productivity and drive customer growth.

Role Overview

• We're looking for a Technical Leader to shape the next generation of intelligent personalization systems. This role offers the opportunity to define architectural strategy, lead transformative initiatives, and work at scale on personalization platforms infused with machine learning and semantic intelligence.

As a Principal Engineer at Beyond, you’ll:

• Lead the architecture and evolution of scalable, high-performance personalisation backend systems, including the ingestion and processing of data to create AI driven personalization pipelines.
• Drive cross-functional initiatives to establish industry leading personalization technologies, leveraging traditional and advanced Machine Learning models, as well as large language models (LLM) to improve user experience through personalisation.
• Define strategies to enhance the performance, reliability, and observability of personalization services, ensuring low-latency, high-availability systems.
• Design and implement frameworks for evaluating personalisation quality through both offline metrics and live A/B experimentation.
• Champion engineering best practices and mentor engineers across teams, raising the bar for code quality and system design.
• Shape long-term technical direction by staying ahead of trends in personalisation and recommendation technologies, distributed systems, and bringing these innovations into production.

Things that will make you stand out:

• Degree in Computer Science, Engineering, or a related technical field.
• 8+ years of experience designing and leading the development of large-scale distributed backend systems.
• Hands-on experience with personalization infrastructure and/or recommendation engines is a strong advantage.
• Deep expertise in Collaborative Filtering (user-item, item-item), Content-Based Filtering, and Matrix Factorization techniques (SVD, ALS).
• Experience developing advanced models, such as:
• Deep Learning Architectures: Including Two-Tower models for scalable candidate retrieval, and sequence-aware models like Transformers or RNNs for session-based recommendations.
• Hybrid Models: Combining multiple approaches (e.g., collaborative and content-based) to overcome their individual limitations.
• Developing specialized Techniques, such as:
• Multi-Armed Bandits (for exploration vs. exploitation)
• Learning to Rank (LTR) for optimizing ordered lists
• Generating embeddings for users and items
• Mastery of Python and its core ML ecosystem, including TensorFlow, PyTorch, Scikit-learn, and XGBoost.
• Demonstrable experience building robust APIs (REST, GraphQL) and operating in modern cloud environments (GCP, AWS), using Kubernetes, Docker, CI/CD, and observability tools.
• Proven ability to lead and influence engineering direction across teams and functions.
• Strong communication skills and the ability to align diverse technical stakeholders around a cohesive vision.

Nice to Have

• Specialisation in recommendation-related ML areas such as deep Learning for sequential Data, reinforcement learning, causal inference, ML System Architecture and GNN (Graph Neural Networks).
• Experience integrating LLMs, developing custom model architectures, or deploying machine learning solutions in production to enhance personalization relevance.

Having been named among the Sunday Times Best 100 Companies, we believe culture plays a large role in what we offer as an organization. We actively promote diversity in all its forms across our Studios, and we proudly, passionately, and proactively strive to create a culture of inclusivity and openness for all our employees.

Beyond is committed to welcoming everyone, regardless of gender identity, orientation, or expression. Our mission is to remove exclusivity and barriers and encourage new thinking and perceptions in a space of belonging. It is not about race, gender, or age, it is about people. And without our people being their most creative and innovative selves, we are nothing.