Senior MLOps Engineer

Senior MLOps Engineer Appodeal is a dynamic US-based product company with a truly global presence. We have offices in Warsaw, Barcelona and Parkland (FL), along with remote team members located around the world. Our company thrives on diversity, collaboration, and innovation, making us a leader in the mobile app monetization space. At Appodeal, we’re more than just a company—we’re a team united by a common mission: Help people discover and grow their talents through products that enable successful mobile app businesses! We take pride in our cutting-edge product and our internationally dispersed team of talented professionals. Here’s what we value, and what we hope you do too: - Continuous Learning and Growth: We are passionate about learning, growing personally, and building rewarding careers. - Making an Impact: We are committed to building a history-defining company that leaves a lasting impact on the mobile app industry. - Solving Exciting Challenges: We tackle complex problems every day, supported by a team of world-class professionals and mentors. - Enjoying the Journey: We believe in having fun while working toward our goals. We are looking for a Senior MLOps Engineer to add to our Data team in Barcelona. Join the User Acquisition MLOps team that builds the core ML backbone of Appodeal. We design and run the systems that power real-time predictions at massive scale, where every millisecond matters. Our work directly drives thousands of bidding operations each second, supporting a high‑throughput, low‑latency inference platform used across the company. You will help shape and evolve a modern ML platform built around Databricks, MLflow, Unity Catalog, GitHub Actions, and deep integrations with our Predictor service. This means solving real engineering challenges: scaling training pipelines, optimizing GPU workloads, ensuring safe and automated model promotions, and keeping online inference reliable under extreme load. You will collaborate daily with Data Science, Data Engineering, Runtime, DevOps, and Product, and you will fully own the systems and projects you touch. This is a role for engineers who like autonomy, impact, and building things that matter. Responsibilities: - Design, operate, and improve the ML platform, including Databricks workflows for training, MLflow and Unity Catalog for model management, CI/CD pipelines using GitHub Actions and Databricks Asset Bundles, and integration with the runtime inference layer. - Support data scientists in developing and maintaining end-to-end training pipelines, covering data processing, feature transformations, ML model training on GPUs, and distributed training setups to ensure efficient and scalable workflows. - Ensure reliable and safe model inference by validating models before promotion, checking metadata compatibility, monitoring latency, and supporting model evaluation flows. - Maintain strong ML observability, including online and offline monitoring, data and feature parity checks, and automated validation of model performance in production. - Develop internal tools and APIs that enable DS teams and account managers to experiment, validate, and promote models efficiently while reducing operational friction.