Senior PM: Recommendation Engine & Ads ML

Lever, Inc.; United States; Remote; USD 150,000 - 250,000; Full time

Benefits offered by this job

Medical, dental, vision

Flexible time off

Career development opportunities

Job summary

Xsolla seeks a Sr. Technical Product Manager to own the ranking engine behind its Ads products, shaping what offers players see and in what order.

You will define success metrics, set objectives, and guide cross-functional teams through model-first decision making. You'll collaborate with ML engineers, data platforms (Snowflake, BigQuery, Spark), and analytics stakeholders to translate model performance into revenue outcomes while maintaining a people-first approach.

Qualifications

• 6+ years in product management with domain in ranking/recommendation systems.
• Deep understanding of experiment design, inference, and AB testing.
• Hands-on experience with ML and data platforms.
• Ability to move model changes to production via controlled experiments.
• Strong writing and stakeholder management skills.

Responsibilities

• Own the recommendation engine as a product: ranking, relevance, and the model roadmap.
• Set objective and constraints for the ranker including guardrails.
• Define metrics and readouts used by the team and stakeholders.
• Collaborate with ML frameworks, A/B testing, and experiment design.
• Align ranking with pricing, identity, and telemetry in ads roadmap.
• Communicate findings to technical and non-technical audiences.

Skills

Recommendation systems

Ranking

Product management

Experiment design

Stakeholder communication

SQL

ML platforms

Data analysis

Education

Bachelor's or Master's in Computer Science, Engineering, Statistics, or Economics

Tools

Snowflake

BigQuery

Spark

Airflow

dbt

MLFlow

Vertex AI

Feature stores

Job description

Xsolla seeks a Sr. Technical Product Manager to own the ranking engine behind its Ads products, shaping what offers players see and in what order.

You will define success metrics, set objectives, and guide cross-functional teams through model-first decision making. You'll collaborate with ML engineers, data platforms (Snowflake, BigQuery, Spark), and analytics stakeholders to translate model performance into revenue outcomes while maintaining a people-first approach.