首席/资深数据科学家
Principal / Staff Data Scientist
关于您
我们正在寻找一位经验丰富的首席机器学习工程师加入我们的全球机器学习团队。在此职位中，您将推动我们机器学习生态系统的创新，设计先进的机器学习解决方案，并在全球范围内指导初级机器学习工程师。您将在塑造我们的技术方向中发挥关键作用——领导复杂的机器学习项目，提升工程标准，并指导团队构建可扩展、生产就绪的机器学习系统。
如果您有抱负，热衷于解决具有挑战性的技术问题，热爱培养人才，并对影响视频游戏行业的机器学习/AI未来充满热情，那么这可能是适合您的职位。
关于我们的公司
Xsolla 是一家全球性商业公司，提供强大的工具和服务，帮助开发者解决视频游戏行业固有的挑战。从独立开发到AAA级别，公司与Xsolla合作，帮助他们资助、分发、营销和变现他们的游戏。基于对视频游戏未来的信念，Xsolla致力于汇聚机会，并持续为创作者提供新的资源。总部和注册地均位于美国加利福尼亚州洛杉矶，Xsolla作为交易商负责运营，已帮助超过1500+位游戏开发者触达更多玩家并实现业务增长。随着更多盈利路径和获胜方式的出现，开发者拥有享受游戏所需的一切。
更多信息，请访问 xsolla.com。
福利：
我们热衷于为团队营造支持性的环境，因此通过全面的福利计划优先关注员工及其家庭的身心健康。这包括100%由公司支付的医疗、牙科和视力保险，无限灵活休假，以及每位美国员工的个性化职业发展路线。通过投资培训和教育机会来促进专业发展，我们确保团队在个人和职业上都能茁壮成长。我们不仅是在打造一家企业，更是在培育一个重视创造力、协作和游戏变革力量的社区。
平等就业机会声明：
Xsolla 是一家平等就业机会雇主。我们庆祝多样性，并致力于为所有员工创造一个包容的环境。我们不基于种族、肤色、宗教、性别、国籍、年龄、残疾或性取向进行歧视。
查看英文原文
ABOUT YOU
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.
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.
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 US 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 Data Scientist position, 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
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 careers@xsolla.com.
Requirements:
Modeling Depth
- 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).
Technology Familiarity
- 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).
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.