Senior Machine Learning Engineer, User Signal & Ads
$185k - $235k • Bellevue, Washington, United States • Full-time
Posted 1mo ago
Job Location
Bellevue, Washington, United States
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
NewsBreak is seeking a Senior Machine Learning Engineer to join the User Signal team, which is central to their in-house advertising platform. This role involves designing and building the data and ML systems that transform raw user signals into production targeting and bidding features. You will own significant pieces of the signal-to-model pipeline end-to-end, from defining and building features at scale to developing models for user understanding, and applying these predictions directly into ads targeting, bidding, and ranking models to drive measurable lift. This is a hands-on, high-ownership role that blends ML modeling, large-scale data engineering, and production ML systems, requiring close collaboration with Ads, Data, and Infra teams, and driving technical direction.
Responsibilities
- Design, implement, and own offline and online feature pipelines (batch + streaming) to transform raw user events into high-quality targeting and bidding features.
- Build and improve models such as identity prediction, user/content embeddings, intent and conversion prediction, and signal-quality/value models.
- Integrate identity-prediction results and other user signals directly into ads targeting, bidding, and ranking models, owning the impact on revenue.
- Manage the full model lifecycle: data preparation, feature engineering, training, offline/online evaluation, deployment, monitoring, and iteration with A/B testing and business metrics.
- Ensure features and model outputs are available online with the freshness and low latency required by high-QPS real-time bidding.
- Identify and address gaps, biases, and freshness issues in user signals; build data quality, labeling, and validation systems.
- Collaborate with Ads ranking/bidding, Data, and Platform teams to align signal and feature design with downstream needs.
- Provide technical leadership, drive design reviews, set best practices, and mentor engineers.
Requirements
- Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, or a related quantitative field (or equivalent practical experience).
- 5+ years of industry experience building and shipping ML models in production.
- Strong foundation in machine learning: feature engineering, supervised learning, embeddings/representation learning, and offline + online evaluation.
- Proficiency in Python and an ML stack (e.g., PyTorch or TensorFlow, scikit-learn, pandas/NumPy).
- Hands-on experience with large-scale data processing for ML (e.g., Spark, Flink, SQL/Presto/Trino) and building production feature or training-data pipelines.
- Experience taking models from idea to production: training, deployment, monitoring, and iteration based on metrics and A/B tests.
- Strong analytical and problem-solving skills, with the ability to reason about model behavior, data quality, and business impact.