Senior Machine Learning Engineer

Realize your potential by joining the leading performance-driven advertising company and a proud Great Place to Work® Certified employer in the US

As a Sr Machine Learning Engineer on Taboola’s R&D Team in Downtown Los Angeles, utilizing some of the latest technology and tools, you will work on the recommendation and ranking algorithms that drive Realize — Taboola's performance advertising platform serving 600M+ daily active users.

The models you build directly influence campaign performance and revenue outcomes for advertisers worldwide.

To thrive in this role, you'll need:

• Bachelor or advanced degree in a relevant field, ideally Computer Science, Electrical Engineering, or Computational Economics

• 5+ years of hands-on experience in Python and Java

• Proficiency with ML frameworks (e.g., PyTorch, Tensorflow)

• Experience with recommendation systems, ranking algorithms, or personalization at scale

• Experience taking end-to-end ownership of ML systems: design, build, ship, measure, and maintain — using AI-assisted “vibe coding” tools (e.g., Cursor, Claude, GitHub Copilot)

• Experience building automated evaluation harnesses and test frameworks for ML systems — defining benchmarks, baselines, and guardrails that let a team ship confidently and repeatedly

• Ability to communicate technical findings clearly, and to collaborate effectively across teams (including early morning or evening syncs with our Tel Aviv team)

Bonus points if you have:

• Experience with Karpathy's autoresearch (MIT), AutoML or any other agentic tools for ML experiments

How you’ll make an impact:

• Design and build predictive customer behavior models for targeting and personalization

• Implement the applicable Machine Learning or statistics based algorithm for prediction and optimization and deliver the trained model to production

• Take end-to-end ownership: design, build, ship, measure, and maintain models and the services around them—rapidly prototyping and delivering complete projects/products using AI-assisted “vibe coding” workflows.

• Act as a Harness Engineer: build the evaluation harnesses, automated testing frameworks, benchmarks, and guardrails that let the team experiment, measure model quality, and ship AI/ML systems safely and repeatedly, following a TDD process.

• Present findings to the product team and technical team leads in a clear and actionable way.

• Build and maintain code to populate HDFS, Hadoop with log from Kafka or data loaded from SQL production systems

• Design, build and support algorithms of data transformation, conversion, computation on Hadoop, Spark and other distributed Big Data Systems