Senior Research Engineer
- 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).
- 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.
- 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
- 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
- Opportunity to build technology that will transform millions of shopping experiences.
- Real ownership and impact in shaping product and company direction.
- A dynamic, collaborative work environment with cutting-edge ML challenges.
- Competitive compensation and equity in a rapidly growing company.
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