Staff ML Specialist

The core responsibilities for the job include the following:
ML Development and Deployment:
Design and develop cutting-edge models for predicting ad outcomes, bidding decisions, budget pacing, and SKU/ad selection.
Build intelligent automation systems for campaign management that adapt in real-time to advertiser and platform feedback.
Develop generative models to optimise ad creatives and improve user engagement across formats.
System Architecture and Optimisation:
Own the architecture of core components like model pipelines, simulation frameworks, and personalisation layers within the ad platform.
Drive research into long-term value modelling, multi-touch attribution, and campaign lifecycle optimisation.
Cross-Functional Impact:
Collaborate with Product and Engineering to design features that are ML-first and measurable.
Act as the primary technical stakeholder for experimentation, metrics design, and long-term roadmap planning.
Thought Leadership and Innovation:
Explore and prototype novel approaches using reinforcement learning, RLHF, contrastive learning, or LLMs for advertiser assistance or campaign agents.
Publish internal whitepapers or contribute to external publications and IP generation when applicable.
Requirements:
Strong understanding of learning-to-rank, bandits and exploration strategies; representation learning / embeddings; auction systems and ad marketplaces; multi-objective optimisation; real-time inference; latency-sensitive model serving; and model monitoring in production environments.
Fluency in Python and ML frameworks like PyTorch, TensorFlow, and XGBoost and libraries like LightGBM and Scikit-learn.
Expertise in large-scale data processing with PySpark, SQL, etc.
Experience with a strong command of A/B testing design, incrementality measurement, and online experimentation in ad tech systems.

Experience
9-13 yrs