Senior Machine Learning Engineer

We are looking for a Senior Machine Learning Engineer to join Expedia Group’s Machine Learning Engineering team. You will be a senior technical contributor on a team that architects, builds, and operates the infrastructure for deploying ML solutions, managing data pipelines, and optimizing compute resources for our ranking problems, recommendation engines, and pricing optimization systems. Your work will be critical in shaping how our ML models are designed, deployed, and scaled in production environments, and in elevating the engineering capabilities of the team around you.

This is a high-impact role for a deeply experienced ML engineer who brings expertise across software engineering, distributed systems, and machine learning operations (ML Ops). You will take end-to-end ownership of complex ML systems, drive architectural decisions, and partner closely with ML scientists and product stakeholders to deliver production-grade solutions at scale.

This role is well-suited to someone with deep, proven experience in at least two of the following: software engineering, data engineering, distributed systems, or applied machine learning - with a track record of delivering in production. You are comfortable navigating ambiguity, making technical trade-offs with business context in mind, and driving alignment across teams. You operate with a high degree of autonomy and are expected to set a technical bar for those around you through design, code, and mentorship.

We welcome candidates who are strong, language-agnostic problem solvers and passionate about building robust ML systems, even if you don’t meet every single requirement listed below. If you believe you can do the job and are excited to grow with us, we’d love to hear from you.

• Architect and own end-to-end ML infrastructure for training, deployment, and serving across batch and real-time environments.
• Define and drive technical standards for ML systems, including reliability, observability, and performance benchmarks.
• Lead the design and implementation of scalable data pipelines for large-scale feature engineering and model training.
• Own system performance and reliability across the ML platform, proactively identifying and resolving bottlenecks.
• Establish and evolve ML Ops practices, including CI/CD pipelines, monitoring, alerting, and A/B testing frameworks.
• Serve as a senior technical partner to ML scientists, leading the model development-to-production workflow for critical systems.
• Mentor junior and mid-level engineers, lead design and code reviews, and raise the technical bar across the team.
• Evaluate and integrate emerging technologies, contribute to roadmap decisions, and communicate technical strategy to diverse stakeholders.

• You hold a Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
• You have 5+ years of experience in Software, Data, or ML engineering roles, with a clear track record of delivering production ML systems.
• You bring strong problem-solving skills, deep proficiency in Python, and hands‑on experience with ML frameworks like Tensor Flow or PyTorch.
• You have a deep understanding of ML algorithms, model architectures, and the infrastructure required to build scalable, reliable ML systems.
• You are proficient with cloud platforms (e.g., AWS, GCP), containerization (Docker, Kubernetes), and distributed data systems (e.g., Spark, Kafka).
• You have proven experience with ML model serving technologies (e.g., MLflow, Tensor Flow Serving), CI/CD tooling, and ML platform design.
• You have a demonstrated ability to mentor engineers, lead technical discussions, and drive cross‑functional alignment.

The total cash range for this position in Madrid is €70,000.00 to €98,000.00. Employees in this role have the potential to increase their pay up to €, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual’s knowledge, skills, and experience.

Pay ranges may be modified in the future.