Senior MLOps\ML Platform Engineer

This is an exciting opportunity to join a newly launched ML initiative within a leading European fashion and retail company, where cutting-edge machine learning ideas are turned into real, production-ready solutions.

The role focuses on building and validating Machine Learning Proofs of Concept (POCs) that shape how ML is developed and scaled across the organization. It is a platform-level position spanning evaluation, implementation, and early production rollout. You will work in small, cross-functional project groups (together with applied scientists and software engineers) to design, build, and operationalize ML solutions that can later be reused and scaled by multiple teams.

Responsibilities:

• Design, build, and validate ML platform POCs across multiple use cases.
• Work closely with Applied Scientists, ML Engineers, and Platform teams to deliver end-to-end ML workflows.
• Implement and operate ML pipelines for training, inference, deployment, and monitoring.
• Run and optimize ML workloads on Kubernetes, including GPU-based and multi-tenant environments.
• Evaluate and integrate ML platform tools and infrastructure into a shared, scalable platform.
• Support the early production rollout and integration into the existing ecosystem.
• Define best practices, governance, and onboarding standards for teams adopting the platform.
• Ensure reliability, security, and performance of ML systems in production.

Skills Required

Must-Have:

• Strong experience building and operating production-grade ML platforms or large-scale data/ML systems on cloud infrastructure.
• Solid background in distributed systems, including containers (Docker), orchestration (Kubernetes), and streaming / batch processing (Kafka, Spark, Flink, etc.).
• Experience designing and operating scalable, low-latency, or high-throughput systems.
• Strong understanding of reliability, monitoring, and safe deployment practices (SLOs, incident response, capacity planning).
• Experience embedding security, IAM, and governance into platform workflows.
• Ability to evaluate, integrate, and operate multiple platform components into a coherent ML platform.
• Strong communication skills, with the ability to produce architecture designs, POC findings, and technical recommendations.

Nice-to-Have:

• Experience with Kubernetes-first ML systems, including:
• Running ML workloads on Kubernetes (EKS preferred)
• Multi-tenant and GPU-based environments
• Experience with enterprise ML platforms (e.g. Databricks, Domino, ClearML).
• Experience with feature platforms / feature stores (Feast, Hopsworks, etc.).
• Familiarity with governance and compliance in regulated ML environments.
• Experience onboarding teams to shared platforms.
• FinOps awareness for ML infrastructure costs.
• Focus on developer experience and platform enablement (templates, golden paths, onboarding flows).

Engagement Model: Direct Independent Contractor (Please read carefully)

This is an independent contractor opportunity based on a direct contractual relationship between Zoolatech and the individual service provider.

To facilitate this direct partnership, we engage with professionals who are registered and operate as a sole proprietorship, private entrepreneur, or an equivalent self-employment status in your country.

Please note, our model does not accommodate contracts through third-party intermediaries such as agencies, incubators, or umbrella companies. The essential requirement is your ability to enter into a service agreement and invoice Zoolatech directly. This is not an offer of direct employment

Please note that only candidates whose profiles closely match our requirements will be contacted.