Senior ML Engineer - Real-Time CTR/CVR ML Platform (Equity)

Moloco; Edison (CA); On-site; USD 153,000 - 187,000; Full time

Benefits offered by this job

Medical, dental, vision coverage

401(k) with company match

Paid holidays and Thrive Day off

Flexible Time Off (FTO)

Job summary

Moloco is seeking a Senior Machine Learning Engineer to own production CTR/CVR models within the NEXT platform. You’ll hunt for signals, log data, and iterate from offline to online evaluation in a fast-paced, data-driven environment.

You’ll collaborate with data and pipeline teams to align signals and drive model quality, while building tooling to automate experimentation and debugging. A strong Python background is essential.

Qualifications

• 5+ years of machine learning experience in business-critical environments.
• Experience with data analysis and large-scale prediction or decisioning systems (CTR/CVR, ranking, recommendations).
• Experience writing Python code.
• Comfortable working under ambiguity.
• Bonus: Experience with using LLMs as agents or feature extractors in evaluation or signal-discovery contexts.

Responsibilities

• Own CTR/CVR prediction models end-to-end within NEXT, including modeling, evaluation, feature pipelines, online experimentation, and post-launch ops.
• Identify and incorporate new data sources and signals to improve model performance.
• Design offline evaluation, ship to online A/B testing, and iterate quickly.
• Build agentic tooling to automate experiment debugging and signal discovery.
• Set technical direction for NEXT in collaboration with data and pipeline teams.
• Tackle data-quality instrumentation and ensure train/serve consistency across feature pipelines.

Skills

Machine learning

Data analysis

Large-scale systems

Python

Job description

Moloco is seeking a Senior Machine Learning Engineer to own production CTR/CVR models within the NEXT platform. You’ll hunt for signals, log data, and iterate from offline to online evaluation in a fast-paced, data-driven environment.

You’ll collaborate with data and pipeline teams to align signals and drive model quality, while building tooling to automate experimentation and debugging. A strong Python background is essential.