About Us

We are a VC-backed startup focused on hyper-personalisation, currently in stealth. Inspired by the latest in recommender systems, we are leveraging transformers and GNNs combined with deep reinforcement learning to build engaging customer experiences for in-store retail.

Our mission is to change retail forever. We use advanced AI and our proprietary technology to create hyper-personalised shopping experiences that are both simple and beautiful.

About the Job - Foundation Models for Retail

We are looking for a Senior Research Engineer with experience in advanced machine learning systems to work with our team of industry leading domain experts and engineers to build foundation models for retail shopping.

Key Responsibilities:

• Translate latest ML advances into impactful solutions, validate their effectiveness, and deploy them to production systems.
• Innovate upon state-of-the-art ML research applied to consumer personalisation.
• Optimise machine learning models for performance in cloud environments (e.g., distributed clusters, GPUs).

Progression Timeline:

• Month 1: Implement and evaluate current SOTA models, benchmark against existing internal models, and identify performance bottlenecks in existing implementations for optimisation.
• Month 3: Design and implement a prototype model architecture, achieve quantifiable improvements in model performance metrics, and develop data pipeline components for large-scale training workflows.
• Month 6: Deploy an optimised foundation model meeting production requirements, implement algorithmic improvements reducing training time and memory footprint, and document performance benchmarks with detailed ablation studies.

Essential Qualifications:

• 3-5+ years implementing applied machine learning research in a production setting
• MSc in Computer Science, Machine Learning, or a closely related field
• Strong foundation in machine learning and deep learning algorithms (e.g., transformers, GNNs, supervised/unsupervised learning, reinforcement learning, deep neural networks)
• Excellent Python programming skills with experience in developing and debugging production-level code

Desired Skills (Bonus Points):

• Proven experience in recommender systems, behavioural AI, and/or reinforcement learning.
• Building data pipelines (realtime or batch) & data quality using modern toolchain (e.g., Apache Spark, Kafka, Airflow, dbt).
• PhD in Computer Science, Machine Learning, or a closely related field

What We Offer:

• Opportunity to build technology that will transform millions of shopping experiences
• Real ownership and impact in shaping our product and company direction
• A dynamic and collaborative work environment
• A chance to work with cutting-edge technologies and solve challenging problems
• Competitive compensation
• Equity in a rapidly growing company