Senior Machine Learning Engineer

What you’ll do

Build and deploy machine learning models that improve recommendations, ranking, and personalization, driving measurable impact on user experience and engagement

Own problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deployment

Develop and maintain scalable ML pipelines using tools such as Spark and Airflow to support reliable, high-quality model delivery

Apply modern ML frameworks (e.g. PyTorch or TensorFlow) to design, train, and optimise models in production environments

Contribute to experimentation frameworks, including A/B testing and offline evaluation, to iterate on model performance with an agile mindset

Collaborate cross-functionally with Product and Engineering, working with purpose to translate product questions into ML solutions

Take ownership of delivering high-quality solutions and see work through from insight to impact, balancing speed and rigor

Apply responsible AI practices, ensuring fairness, transparency, and safety are considered in model development and deployment

About You

Typically requires 5–8 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.

Strong experience building and deploying machine learning models in production environments

Proficiency in Python and experience with at least one major ML framework (e.g. PyTorch, TensorFlow)

Experience working with data pipelines and distributed systems (e.g. Spark, Airflow) to support ML workflows

Familiarity with experimentation methodologies such as A/B testing and model evaluation techniques

Ability to collaborate effectively across functions, demonstrating strong ownership and a collaborative mindset

Demonstrates an agile mindset, adapting approaches based on data and evolving priorities while maintaining focus on outcomes

Growing AI fluency, with the ability to independently apply ML techniques and emerging tools (including LLMs) to solve problems responsibly