Nuvei
Fintech
Machinelearningoperationsengineer
“Machine learning operations engineer at Nuvei. Skills: MLOps, Kubernetes, Python, CI/CD. Operate & Develop ML/LLM platforms. Manage object storage, GPUs, autoscaling”
What You'll Achieve.
Reliability; Governance; Cost efficiency; Measurable business impact; Strict latency SLOs; Provide SLAs; Safety events
Industry & Context.
solving complex problems
on-call runbooks, PCI-DSS requirements, data-residency requirements
What They're Looking For.
Must Have
4+ years in DevOps/MLOps/Platform roles building and operating production ML systems (batch and real-time), hands-on with Kubernetes, Docker, Terraform/IaC, and CI/CD, Practical experience with Spark/Databricks and scalable data processing, Proficiency in Python & Bash, Ability to operate DS code and optimize runtime performance, Experience with model registries (MLflow or similar), experiment tracking, and artifact management, Production model serving using FastAPI/Ray Serve/Triton/TorchServe, including autoscaling and rollout strategies, Monitoring and tracing with Prometheus/Grafana/OpenTelemetry; alerting tied to SLOs/SLAs, Solid understanding of PCI-DSS/GDPR considerations for data and ML systems, Operating LLM/agent workloads in production (prompt/config versioning, tool execution reliability, fallback/retry policies), Building/maintaining RAG stacks (indexing pipelines, vector DBs, retrieval evaluation, hybrid search), Implementing guardrails (policy checks, content filters, allow/deny lists) and human-in-the-loop workflows, A testing for models and agents, offline/online evaluation frameworks
Nice to Have
Experience with the Azure cloud environment is a big plus, Payments/fraud/risk domain integrating ML outputs with rule engines and operational systems - Advantage, Familiarity with Databricks Unity Catalog, dbt, or similar tooling
What You'll Do.
Operate & Develop ML/LLM platforms
Manage object storage
Manage cloud environment
Build end-to-end CI/CD for models/agents/MCP
Deliver real-time fraud/risk scoring
Maintain MCP servers/clients
Integrate agents with microservices
Measure operational metrics of ML/LLM
Enforce governance: RBAC/ABAC
Partner with DS on packaging
Lead incident response
How You'll Work.
Team & Collaboration
Partner closely with Data Scientists; Partner closely with Data/Platform Engineers; Partner closely with Product; Partner closely with SRE; Partner with DS on packaging
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