Senior MLOpsML Platform Engineer

Senior MLOpsML Platform Engineer
Zoolatech
jobBoard.filter.role.option.DEVOPS_SRE
Central and Western, Hong Kong, China
7 days ago
Full Time
Onsite
Technology, Information and Media
Job Description
7 days ago
OVERVIEW

RESPONSIBILITIES

REQUIREMENTS

This opportunity is part of a newly launched ML initiative within one of Europe’s leading fashion and retail companies, operating at large scale across multiple markets and serving millions of customers.

The team is building a shared Machine Learning platform that will enable multiple product teams to develop, deploy, and scale ML solutions reliably in production.

This is a platform-level role focused on evaluating, designing, and rolling out reusable ML capabilities across the organization - from proof of concept to early production adoption. The position combines hands-on engineering with architectural input, helping define how ML infrastructure will operate at scale across the company.
• Support and contribute hands-on to multiple ML platform POCs
• Work closely with Applied Scientists, ML Engineers, and internal Platform teams
• Evaluate platform capabilities (GPU training, real-time and batch inference, orchestration, scalability)
• Analyze performance, reliability, and integration with existing systems
• Contribute to key technical decisions (build vs buy, tooling, target stack)
• Support early production rollout and integration into the broader ecosystem
• Help define best practices, governance standards, and onboarding guidelines
• Enable adoption of the platform by initial and scaling teams
• 5+ years building and operating production-grade ML or large-scale data systems on cloud platforms
• Experience with distributed systems (Docker and Kubernetes)
• Experience with streaming or batch processing systems (e.g. Kafka, Spark, Flink)
• Experience designing scalable, low-latency systems in production environments
• Strong understanding of reliability, monitoring, and safe deployment practices
• Experience integrating multiple tools into a coherent, production-ready ML platform
• Ability to contribute to architectural decisions and communicate technical trade-offs clearly
• Experience running ML workloads on Kubernetes (GPU or multi-tenant environments)
• Experience with enterprise ML platforms (e.g. Databricks or similar)
• Experience onboarding teams onto shared platforms and optimizing infrastructure costs

Location:

Other, Central Europe

Seniority:

Senior

Technologies:

Python

Benefits:
• Paid Vacation
• Sick Days
• Floating Holidays
• Sport/Insurance Compensation
• English Classes
• Charity
• Training Compensation
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