Senior Machine Learning Engineer I - ML Production
Booking.com2 days ago
Amsterdam, NetherlandsSenior
Responsibilities
- Architect, build, and operate scalable, low-latency distributed ML inference services across online, asynchronous, and batch workloads.
- Manage production model deployments, model versioning, feature access, shadow and canary testing, and rollbacks.
- Optimize CPU, GPU, and memory utilization and lead capacity planning to reduce operational costs.
- Operate multi-cloud and on-premise Kubernetes workloads with automated scaling, CI/CD, and infrastructure-as-code practices.
- Implement telemetry including metrics, logs, traces, dashboards, and alerts; maintain SLIs and SLOs and participate in on-call response.
- Partner with ML scientists and engineers to productionize models, improve developer experience, set technical direction, and mentor junior engineers.
Requirements
- Experience deploying and operating machine learning models in production across backend, infrastructure, or SRE domains.
- Proficiency in Java, Scala, JVM languages, or Python with strong backend engineering skills.
- Experience designing distributed systems involving microservices, RPC, queues, streaming, caching, and batch processing.
- Understanding of concurrency, resource management, and server-side profiling.
- Hands-on experience managing containerized Kubernetes workloads in production.
- Experience with cloud or hybrid infrastructure, platform capabilities, infrastructure as code, and CI/CD.
- Experience with observability using SLIs, SLOs, metrics, logs, dashboards, and alerts.
- Understanding of real-time and batch ML inference, model versioning, feature retrieval, and monitoring.
- Familiarity with on-call work, incident response, postmortems, and runbooks.
- Strong cross-team collaboration, English communication, and ability to make pragmatic technical trade-offs.
- Preferred experience with ML serving platforms or runtimes such as Triton, ONNX Runtime, TF Serving, or TorchServe.
- Preferred background in JVM tuning, low-latency systems, GPU scheduling, SRE or platform engineering, multi-cloud or hybrid scale, Spark, Kafka, Flink, Terraform, drift monitoring, or GenAI/LLMs.
Benefits
- Annual paid time off and generous paid leave, including parental, grandparent, bereavement, and care leave.
- Hybrid working with flexible arrangements and up to 20 days per year working from abroad in the home country.
- Industry-leading product discounts of up to 1400 per year, including automatic Genius Level 3 status and Booking.com wallet credit.
- The role does not come with relocation assistance.
Tech Stack
Categories
About Booking.com
Booking.com operates a global online travel platform for booking accommodations, flights, car rentals, and experiences for consumers and business travelers. It earns primarily through commissions and merchant/agency models with hotels, vacation rentals, and other travel partners. Founded in 1996 and headquartered in Amsterdam, it is part of Booking Holdings and serves users and suppliers across hundreds of markets worldwide.