Senior Machine Learning Engineer

Taboola•Los Angeles, CA

6d•Hybrid

About The Position

Taboola is hiring a Senior Machine Learning Engineer for its R&D team in Downtown Los Angeles. The role focuses on recommendation and ranking algorithms for Realize, Taboola’s performance advertising platform, which serves more than 600 million daily active users. Models developed in this role influence advertiser campaign performance and revenue outcomes worldwide. The engineer will build predictive models for customer behavior, targeting, personalization, and optimization, and deliver trained models to production. The role includes end-to-end ownership of ML systems and their surrounding services: designing, building, shipping, measuring, and maintaining them. It also emphasizes rapid prototyping with AI-assisted coding tools and creating evaluation harnesses, automated tests, benchmarks, and guardrails so teams can assess model quality and ship systems safely and repeatedly using a test-driven development process. The position also involves presenting technical findings to product and engineering leads, maintaining data pipelines that populate HDFS and Hadoop with logs from Kafka or data from production SQL systems, and developing and supporting data transformation and computation algorithms on Hadoop, Spark, and other distributed big data systems. The role follows a hybrid schedule with three days in the office.

Requirements

Bachelor’s or advanced degree in a relevant field; Computer Science, Electrical Engineering, or Computational Economics are identified as ideal fields.
At least 5 years of hands-on experience with Python and Java.
Proficiency with machine learning frameworks such as PyTorch or TensorFlow.
Experience with recommendation systems, ranking algorithms, or personalization at scale.
Experience owning machine learning systems end to end, from design and implementation through deployment, measurement, and maintenance.
Experience using AI-assisted coding tools such as Cursor, Claude, or GitHub Copilot.
Ability to build automated evaluation harnesses and test frameworks for ML systems, including benchmarks, baselines, and guardrails.
Ability to communicate technical findings clearly and collaborate effectively across teams, including early-morning or evening syncs with the Tel Aviv team.

Nice To Haves

Experience with Karpathy’s autoresearch (MIT), AutoML, or other agentic tools for ML experiments.

Responsibilities

Design and build predictive customer behavior models for targeting and personalization.
Implement machine-learning- or statistics-based algorithms for prediction and optimization, and deliver trained models to production.
Own models and their supporting services end to end, including design, building, shipping, measurement, and maintenance.
Rapidly prototype and deliver complete projects or products using AI-assisted coding workflows.
Build evaluation harnesses, automated testing frameworks, benchmarks, and guardrails for experimentation and safe, repeatable delivery of AI/ML systems, following a TDD process.
Present findings clearly and actionably to product teams and technical team leads.
Build and maintain code that populates HDFS and Hadoop with logs from Kafka or data loaded from production SQL systems.
Design, build, and support data transformation, conversion, and computation algorithms on Hadoop, Spark, and other distributed big data systems.