Machine Learning Engineer
Montreal
Xsolla
Find out how you can launch, monetize and scale your video games worldwide, with no upfront costs, using Xsolla's comprehensive suite of tools and services.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.
NICE TO HAVE
- Experience in data pipelines and analytics for video-game development
- Experience in Advertising industry
- Experience in online businesses where transactions happen without human intervention.
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Architecture AWS Azure CI/CD Data pipelines Deep Learning Docker Engineering Feature engineering GCP Kanban Kubeflow Kubernetes Machine Learning MLFlow ML models MLOps NumPy Pandas Pipelines Privacy Python PyTorch SageMaker Scala Scikit-learn Spark Statistical modeling Statistics TensorFlow Vertex AI XGBoost
Perks/benefits: Career development Flex vacation Health care Unlimited paid time off
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