Senior Technical Product Manager, Advertising ML

Xsolla

$150K — $250K *
US-AnywhereRemote in United States
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 6+ years in product management, with 3+ years owning a recommendation or ranking system in production.
  • Deep understanding of experiment design metrics, including sample ratio mismatch and multiple-comparison correction.
  • Working knowledge of classification, regression, and how model objectives influence behavior.
  • Hands-on experience with ML and data platforms such as Snowflake, BigQuery, and Spark.
  • Proven record of implementing models into production through controlled experimentation.
  • SQL proficiency and ability to read application code for verification purposes.
  • Excellent written communication skills for technical and non-technical audiences.

Responsibilities

  • Own the recommendation engine product, focusing on ranking and relevance.
  • Define optimization objectives, constraints, and success metrics for ranking quality.
  • Establish comprehensive metric definitions for team assessments and evaluations.
  • Collaborate on machine learning frameworks and experimental design requirements.
  • Analyze and communicate model performance to business stakeholders.
  • Integrate ranking insights into the broader advertising product roadmap.

Benefits

  • 100% company-paid medical, dental, and vision plans.
  • Unlimited Flexible Time Off.
  • Personalized career roadmap for professional development.
  • Training and educational opportunities for ongoing growth.
Full 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.
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.
SALARY RANGE

$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.

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