Job Description
Xsolla seeks a Machine Learning Engineer to bridge business and data, optimizing monetization for partners. Responsibilities include leading ML projects, overseeing Kanban processes, collaborating with cross-functional teams, designing ML solutions, implementing new technologies, mentoring junior engineers, and collaborating with data engineers and scientists. The ideal candidate possesses strong proficiency in ML frameworks (TensorFlow, PyTorch, etc.), cloud platforms (AWS, GCP, Azure), MLOps practices, data preprocessing skills, and strong programming skills in Python. Experience deploying ML models to production and optimizing inference latency is crucial.
Good To Have:
- Experience with SageMaker, Vertex AI, or Azure ML
- Familiarity with MLflow, Kubeflow, or Airflow
- Understanding of distributed computing (Ray or Dask)
Must Have:
- Proficiency in ML frameworks (TensorFlow, PyTorch)
- Cloud platform experience (AWS, GCP, Azure)
- MLOps practices and CI/CD pipelines
- Data preprocessing and feature engineering expertise
- Strong Python programming skills
- Production ML model deployment experience
Perks:
- 100% company-paid medical, dental, and vision
- Unlimited Flexible Time Off
- Personalized career roadmap
- Professional development opportunities
ABOUT US
At Xsolla, we believe that great games begin as ideas, driven by the curiosity, dedication, and grit of creators around the world. Our mission is to empower these visionaries by providing the support and resources they need to bring their games to life. We are committed to leveling the playing field, ensuring that every creator has the opportunity to share their passion with the world.
Headquartered in Los Angeles, with offices in Berlin, Seoul, and beyond, we partner with industry leaders like Valve, Twitch, and Ubisoft to clear the paths for innovation in gaming. Our global reach spans over 200 geographies, offering more than 700 payment methods in 130+ currencies.
Longevity Opportunity Vision Enjoy the game!
ABOUT YOU
We are seeking a Machine Learning Engineer that is a thinker and a hands-on problem solver who bridges the gap between business and data. You are skilled at translating what are the business constraints, and applying the best models to get the best monetization for our partners. You will collaborate with cross-functional teams including product manager and ad operations to understand requirements, define objectives, and deliver impactful solutions. Adept in statistical modeling, machine learning, and data storytelling, they ensure that insights are not just technically sound but aligned with real-world business needs. While you will have data engineer partners, you are self sufficient and able to develop models end to end and put them into production.
RESPONSIBILITIES
- Leads and supports multiple Machine Learning projects, ensuring alignment with business objectives and data needs.
- Oversees the Kanban process for managing ML model development, deployment, and maintenance.
- Engages in technical discussions both within the company and with external data partners, fostering collaboration and knowledge sharing.
- Drives the design and architecture of machine learning solutions by deeply understanding data usage and identifying opportunities to integrate new data sources.
- Implements emerging technologies and methodologies in machine learning, ensuring state-of-the-art solutions and continuous innovation.
- Mentors and guides junior ML engineers, promoting best practices, scalability, and efficiency in model development.
- Collaborates closely with data engineers and scientists to enhance ML workflows, ensuring models are reliable and production-ready.
REQUIREMENTS
- Strong proficiency in ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, XGBoost, and deep learning architectures.
- Experience with cloud platforms (AWS, GCP, Azure) and deploying ML models using SageMaker, Vertex AI, or Azure ML.
- Familiarity with MLOps practices, including model versioning, CI/CD pipelines for ML (e.g., MLflow, Kubeflow, Airflow), and monitoring deployed models.
- Expertise in data preprocessing and feature engineering, using tools such as Pandas, NumPy, and Apache Spark.
- Strong programming skills in Python (preferred) or Scala, with experience in containerization tools like Docker and Kubernetes.
- Understanding of distributed computing and parallel processing frameworks such as Ray or Dask for scalable ML workloads.
- Experience in deploying ML models to production, optimizing inference latency, and ensuring model robustness in real-world applications.
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.
By submitting the following job application form, you consent to Xsolla processing your data for career-related inquiries and potential employment opportunities. We process your data in accordance with this Xsolla Privacy Notice for Job Applicants. Please direct any inquiries regarding your data privacy to careers@xsolla.com.
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