Senior ML Engineer: Real-Time User Signals for Ads

NewsBreak; Bellevue (KY); On-site; USD 185,000 - 235,000; Full time

Benefits offered by this job

Health, dental, and vision

401(k)

Paid time off

FSA/HSA

Team activities budget

Job summary

NewsBreak in the US is seeking a Senior Machine Learning Engineer to design and build data and ML systems that turn raw user signals into production targeting features for ads.

This hands-on role combines ML modeling, large-scale data engineering, and production ML systems, owning features from ingestion to online serving with low latency and measurable revenue impact.

You will collaborate with Ads, Data, and Infra teams, drive technical direction, mentor engineers, and raise the bar for the team.

Qualifications

• Bachelor’s or Master’s degree in CS/ML/Statistics or related field.
• 5+ years of industry ML engineering experience.
• Strong foundation in ML: feature engineering and evaluation methods.
• Proficiency in Python and ML stack (PyTorch/TF, scikit-learn).
• Experience with large-scale data processing for ML.

Responsibilities

• Build user-signal features at scale (batch + streaming).
• Develop identity-prediction and related user understanding models.
• Apply model outputs inside ads targeting, bidding, and ranking models.
• Own the model lifecycle: data prep, training, deployment, monitoring, A/B testing.
• Bridge modeling and serving across feature stores and serving infra.
• Improve signal quality and coverage with data quality and validation systems.
• Collaborate cross-functionally with Ads, Data, and Platform teams.
• Provide technical leadership and mentor engineers.

Skills

Python

ML modeling

Feature engineering

A/B testing

SQL

PyTorch

TensorFlow

Big data concepts

Communication

Education

Bachelor’s or Master’s degree in Computer Science/ML/Statistics

Tools

Spark

Flink

Presto/Trino

Kafka

Job description

NewsBreak in the US is seeking a Senior Machine Learning Engineer to design and build data and ML systems that turn raw user signals into production targeting features for ads.

This hands-on role combines ML modeling, large-scale data engineering, and production ML systems, owning features from ingestion to online serving with low latency and measurable revenue impact.

You will collaborate with Ads, Data, and Infra teams, drive technical direction, mentor engineers, and raise the bar for the team.