Machine learning engineer in inference platforms

Booking; Amsterdam; Hybrid; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Product discounts

Genius Level 3 status

Booking.com wallet credits

Job summary

Booking.com ищет инженера по ML Platform для проектирования, развёртывания и эксплуатации масштабируемых ML-сервисов с нулевой задержкой и высоким уровнем надёжности. Роль предполагает работу в гибридном формате в Амстердаме, взаимодействие с ML научными сотрудниками и инженерами.

Кандидат должен иметь сильные навыки backend, опыт с Kubernetes и облачными/производственными средами, а также владение инструментами CI/CD и IaC. Условия труда включают гибридный график и конкурентное вознаграждение.

Qualifications

• Опыт развёртывания и эксплуатации ML моделей в продакшене.
• Опыт разработки backend на Java, Scala или Python.
• Понимание распределённых систем (микросервисы, очереди, стриминг).
• Опыт работы с Kubernetes в продакшене.
• Навыки observability: метрики, логи, алерты.

Responsibilities

• Проектирование и развёртывание масштабируемых ML-сервисов.
• Оптимизация затрат на вычисления и управление ресурсами.
• Работа с мультиоблачной/обон-локальной инфраструктурой и IaC.
• Сотрудничество с учёными ML и инженерами.

Skills

Backend-разработка

Java/Python

Распределённые системы

Kubernetes

наблюдаемость

CI/CD

Английский язык

Tools

Docker

Terraform

Prometheus

Grafana

Job description

Описание:

At Booking.com, 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.

Задачи:

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.

Требования:

• 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.


• Будет плюсом: Experience with ML serving platforms, runtimes (Triton, ONNX Runtime, TF Serving, TorchServe), or gateways;


• Будет плюсом: Background in JVM tuning, low-latency systems, GPU scheduling, or SRE/platform engineering;


• Будет плюсом: Familiarity with multi-cloud/hybrid scale, Spark/Kafka/Flink, Terraform, drift monitoring, or GenAI/LLMs

Условия:

• 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 Booking.com wallet credit

This role does not come with relocation assistance.