Staff Machine Learning Engineer, App Ads Modeling

About the role

A staff-level engineering role in an ads ranking organisation, improving machine learning powered ad ranking through better model architectures, contextual embeddings and conversion-optimised modelling.

What you will do

• Design and train advanced models such as deep neural networks and transformers for ad ranking
• Develop and optimise features including embeddings, contextual signals and cross-session behaviour
• Partner with product, infrastructure and data teams on model deployment and performance analysis
• Mentor other machine learning engineers and spread modelling best practices
• Help shape long-term modelling direction across domains such as conversion, app ads, shopping and brand

What they look for

• Strong deep learning and framework skills with TensorFlow or PyTorch
• Background in recommendation systems, ads ranking or similar areas
• Experience with large-scale datasets and complex feature pipelines
• Strong experimentation and problem-solving abilities
• Knowledge of state-of-the-art models for ads or recommendation systems and of the ads or recsys funnel

Nice to have

• Experience with conversion modelling, app ads or performance and brand ads
• Experience in ads marketplaces at peer companies
• Publications, patents or industry contributions in applied machine learning or ranking

Benefits

• Fully remote opportunity, with office locations available for hybrid or onsite work