Senior Technical Product Manager, App Performance Advertising

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

Benefits offered by this job

Medical, dental, and vision insurance

Flexible time off

Career development and training

Job summary

Xsolla is seeking a Sr. Technical Product Manager to own the recommendation engine for our ads products. You will set the ranking objectives, constraints, and guardrails, and tie model performance to revenue.

You will collaborate with ML, data science, and commercial teams to define metrics, run controlled experiments, and drive the roadmap for pricing, identity, and event telemetry integration within ranking.

Qualifications

• 6+ years in product management with 3+ years owning a recommendation or ranking system.
• Deep understanding of experiment design, power calculations, and A/A testing.
• Hands-on ML and data platforms experience.
• Experience moving model changes into production via controlled experiments.
• Knowledge of performance advertising economics and ad tech ecosystems.

Responsibilities

• Own the recommendation engine and ranking as a product.
• Define objective, constraints, guardrails for the ranker.
• Define metric definitions and readouts for the team.
• Collaborate with ML frameworks, experiment design, and rollback triggers.
• Collaborate with DS on readouts to business stakeholders readout.
• Contribute the ranking perspective to the wider ads roadmap.

Skills

Recommendation systems

Ranking systems

Experiment design

ML frameworks

SQL

Stakeholder communication

Education

Bachelor's or Master's in CS/Engineering/Statistics/Economics

Tools

Snowflake

BigQuery

Spark

Airflow

dbt

MLFlow

Vertex AI

Feature stores

Job description

ABOUT YOU

You are a technical product manager who owns what a model optimises for, not just the roadmap around it. You have real depth in recommendation and ranking systems, and you will own the recommendation engine behind the Xsolla Advertising Products: the ranking that decides which offers millions of players see, and in what order.

You hold the bar high for how decisions get made. You can read a readout and say plainly what it does and does not support. You connect model performance to revenue without overclaiming, and you bring a low-ego, people-first approach to work that spans ML, analytics, ads operations, and commercial teams.

If you are excited about using ML to build building the next generation of advertising, rewards and loyalty programs for mobile apps and games we want to hear from you.

ABOUT US

Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game.

For more information, visit xsolla.com.

Responsibilities:

• Own the recommendation engine as a product: ranking, relevance, and the model roadmap. Ranking quality is the product.
• Set the objective the ranker optimises for, the constraints it works inside, and the guardrails and kill conditions that bound it. The target is eCPM today; what comes next is your call.
• Own the metric definitions the whole team measures against, and settle the definitional questions that change the answer: gross against publisher-side RPU, app-load against impression-user denominators, mean of daily values against window totals.
• Collaborate with on ML frameworks, experiment design, hold-outs, including pre-registered decision rules, power calculations, sample-ratio-mismatch checks, A/A validation, multiplicity correction, and named rollback triggers.
• Collaborate with DS on readouts to evaluate model performace and readouts to business stakeholders readout: what the model did, what it cost, and what happens next.
• Contribute the ranking perspective to the wider ads roadmap, including the seams where pricing, identity, and event telemetry meet ranking.

Qualifications & Skills:

• 6+ years in product management, with 3+ years owning a recommendation, ranking, personalization, or relevance system in production.
• Deep understanding of experiment design and inference, including minimum detectable effect, statistical power, sample ratio mismatch, A/A testing, multiple-comparison correction, and pre-registration. You can tell when a readout will not support the claim being made from it, and you say so.
• Working knowledge of the modelling itself: classification and regression, probability calibration, predicted conversion rate, expected-value objectives, and how the choice of objective changes model behavior.
• Hands-on experience with ML and data platforms such as Snowflake, BigQuery, Spark, Airflow, dbt, MLFlow, Vertex AI, and feature stores.
• Proven record of moving model changes into production traffic through a controlled experiment process, rather than shipping on a dashboard reading.
• Knowledge of performance advertising economics and ad tech ecosystems, including eCPM, RPU, bid multipliers, campaign hierarchies, and attribution models.
• SQL you write yourself, and enough comfort reading application code to verify a claim instead of taking it on trust.
• Excellent written communication and stakeholder management across technical and non-technical audiences. Specs, decision records, and readouts are the output of this role, and other teams act on them without you in the room.
• Bachelor's or Master's in Computer Science, Engineering, Statistics, Economics, or a related field.
• Offerwall, rewarded advertising, loyalty and rewards programs and/or mobile app monetization experience is a plus.
• Experience with a two-stage ranking system, where an external service supplies the base order and local logic adjusts it, is a plus.
• Pricing, yield management, or marketplace experience alongside ranking is a plus.

$150,000 - $250,000 a year

Benefits:

We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes 100% company-paid medical, dental, and vision plans, unlimited Flexible Time Off, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we’re not just building a business; we’re cultivating a community that values creativity, collaboration, and the transformative power of play.

Equal Employment Opportunity Statement:

Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law.

We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.

Criminal History Consideration:

For the Sr. Technical Product Manager, we will conduct a background check that may include the following:

Criminal history check

Employment verification

Education verification

Relevance to Job Responsibilities:

The background check is relevant to this position because of the following role responsibilities:

Accessing confidential company data

Ensuring compliance with regulatory requirements

Handling sensitive financial information/managing budgets/accessing funds

Rights Under the Fair Chance Act:

Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact [e-mail].