Vacaturebeschrijving
Senior Machine Learning Engineer I - ML Production in Aemstelredamme, Nederland
Booking.com
- HybrideMix van kantoor en op afstand
- Op locatieWerk vanuit kantoor
- VoltijdStandaard wekelijkse uren
Aemstelredamme, Nederland
About Us: At https://jobeax.com/link/JlXYiB7d5OmofGlA, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world. About the team: The ML Production team in Booking.com’s AI Platform track operates RS, the central inference platform for production workloads. Serving ranking, recommendations, fraud, pricing, and personalization, RS supports deployment, routing, and monitoring across real-time, offline, cloud, and on-premise setups. Focus areas:
- Building reliable, low-latency, high-throughput ML inference services
- Supporting online, async, and batch predictions
- Optimizing system performance, cost efficiency, and resilience
- Enabling safe deployment, rollouts, and lifecycle management
- Streamlining model integration and ops for practitioners
- Advancing cross-environment platform capabilities with portable abstractions
Role Description: As a Senior Machine Learning Engineer I in the ML Production team, you will design, build and operate the platform capabilities that make machine learning inference reliable and efficient at https://jobeax.com/link/JlXYiB7d5OmofGlA scale.
This is a production-focused role. You will work primarily on integrating models into robust services and improving the platform that runs them, rather than developing models in isolation. You will combine machine learning knowledge with strong backend, distributed-systems and platform-engineering skills. You will work mainly with JVM-based services such as Java and Scala, Kubernetes, heterogeneous infrastructure spanning multiple cloud environments and on-premise systems, and our observability stack. You will own services end to end: from requirements and technical design through implementation, deployment, operations and continuous improvement. As a senior engineer, you will lead technically significant work within the team and across partner teams. You will help set the technical direction for platform initiatives, make sound trade-offs between reliability, latency, cost and developer experience, and coach other engineers through design discussions, code reviews and incident follow-up.Key Job Responsibilities and Duties
- Architect, build, and operate scalable, low-latency distributed ML inference services and prediction systems across online, async, and batch workloads.
- Manage production model deployments, model versioning, feature access, shadow/canary testing, and rollbacks.
- Optimize compute utilization (CPU, GPU, memory) and lead capacity planning to minimize operational costs.
- Operate multi-cloud and on-premise Kubernetes workloads with automated scaling, CI/CD, and IaC practices.
- Implement end-to-end telemetry (metrics, logs, traces, alerts), maintain SLIs/SLOs, and participate in on-call response to drive service resilience.
- Partner with ML Scientists and Engineers to productionize models, improve developer experience, and mentor junior team members.
Qualification and skills
- Experience deploying and operating ML models in production across backend, infrastructure, or SRE domains.
- Proficiency in Java, Scala, JVM languages, or Python with strong backend engineering skills.
- Proven background designing distributed systems (microservices, RPC, queues, streaming, caching, batch).
- Solid grasp of concurrency, resource management, and server-side profiling.
- Hands-on experience managing containerized Kubernetes workloads in production.
- Experience with cloud/hybrid infrastructure, core platform capabilities, IaC, and CI/CD.
- Observability experience using SLIs, SLOs, metrics, logs, dashboards, and alerts.
- Understanding of ML serving (real-time/batch inference, versioning, feature retrieval, monitoring).
- Familiarity with on-call, incident response, postmortems, and runbooks.
- Pragmatic, customer-focused mindset for designing reusable platform capabilities and communicating technical trade-offs.
- Strong cross-team collaboration and English communication skills.
Nice to have
- Experience with ML serving platforms, runtimes (Triton, ONNX Runtime, TF Serving, TorchServe), or gateways.
- Background in JVM tuning, low-latency systems, GPU scheduling, or SRE/platform engineering.
- Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, and care leave
- Hybrid working including flexible working arrangements, and up to 20 days per year working from abroad (home country)
- Industry leading product discounts - up to 1400 per year - for yourself, including automatic Genius Level 3 status and https://jobeax.com/link/JlXYiB7d5OmofGlA wallet credit
- Let’s go places together: [How we Hire](#)
- This role does not come with relocation assistance.