We are looking for an accomplished Principal Machine Learning Engineer to join our global ML organization. In this role, you will drive innovation across our machine learning ecosystem, architect advanced ML solutions, and mentor junior ML engineers around the world. You will play a key part in shaping our technical direction—leading complex ML initiatives, elevating engineering standards, and guiding teams as they build scalable, production‑ready machine learning systems.
If you are ambitious, energized by solving challenging technical problems, passionate about developing talent, and excited to influence the future of ML/AI in the video game industry, this could be the perfect role for you.
Requirements:
Advanced Degree in Statistics, machine learning or related areas. Experience in statistics/ML expertise with a track record of leading high-impact data science initiatives at scale of billions of transactions.
Hands-on experience creating, training and fine-tuning models not just integrating hosted model APIs. You should be able to walk through the data, the objective, what broke, and the before/after evaluation numbers, and why the model did not perform as expected.
Experience owning models in production: deployment, monitoring, drift detection, retraining — with real latency budgets, not just research notebooks.
Production experience with classical ML for fraud/anomaly detection, recommendation, or churn/LTV (gradient boosting, deep learning, graph-based models).
Supervised learning, transfer leaning on machine learning as well as neural networks
Basic LLM knowledge, especially how to use it and where not to use it.
MLOps foundations: feature stores, experiment tracking, model registries (MLflow/W&B-class), continuous training pipelines.
Model serving and inference optimization (vLLM-class serving, quantization).
Modeling Depth
Technology Familiarity
Nice-to-Have:
Publications, conference talks, or recognized open-source contributions to training/eval tooling .
Graph-based fraud detection (fraud rings, device/account linkage)..
Gaming, payments, fraud, advertising domain experience.
Hands-on, up-to-date experience with modern AI tools (e.g., Claude, Copilot, Cursor) for code generation, review, and accelerating day-to-day engineering work.
Skills Required
- Advanced degree in statistics, machine learning, or related field
- Proven track record leading high-impact data science initiatives at billion-transaction scale
- Hands-on experience creating, training, and fine-tuning models (not only integrating hosted model APIs)
- Experience owning models in production: deployment, monitoring, drift detection, retraining with latency budgets
- Production experience with classical ML for fraud/anomaly detection, recommendation, or churn/LTV
- Expertise in supervised learning, transfer learning, and neural networks
- Basic knowledge of large language models and appropriate/ inappropriate use cases
- MLOps foundations: feature stores, experiment tracking, model registries (MLflow/W&B-class), continuous training pipelines
- Model serving and inference optimization experience (vLLM-class serving, quantization)
- Publications, conference talks, or recognized open-source contributions to training/eval tooling
- Graph-based fraud detection experience (fraud rings, device/account linkage)
- Domain experience in gaming, payments, fraud, or advertising
- Hands-on experience with modern AI tools for engineering (e.g., Claude, Copilot, Cursor)
Xsolla Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Xsolla and has not been reviewed or approved by Xsolla.
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Fair & Transparent Compensation — Pay is considered fair or good in many cases, with mentions of high salary or being paid well in certain roles and markets. Market-aligned ranges for several U.S. roles indicate base pay is not out of step with peers.
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Healthcare Strength — Health coverage is described as comprehensive for full-time employees and families, with employer-paid medical, dental, and vision noted in some U.S. postings. Positive remarks on medical coverage appear on dedicated benefits pages.
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Leave & Time Off Breadth — Flexible or unlimited paid time off is repeatedly highlighted, alongside parental leave and remote or hybrid flexibility. These elements contribute to an overall package that many view as solid.
Xsolla Insights
What We Do
Xsolla's video game business engine helps game developers and publishers operate more efficiently and sell more games. Serving only the video game industry, Xsolla caters to businesses from indie to enterprise, with solutions that solve the complexities of distribution, marketing, and monetization so developers, publishers, and platform partners. Our goal is to increase your audience, sales and revenue. Headquartered in Los Angeles, with offices worldwide, Xsolla operates as a merchant and seller of record for major gaming entities like Valve, Twitch, Ubisoft, Epic Games, and PUBG Corporation.
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