Build and maintain MLOps automation end-to-end: CI/CD for models and pipelines, environment management, artifact versioning (models, data, prompts, code), and release governance •
Implement and operate model serving infrastructure: deployment patterns (blue/green, canary, shadow), endpoint management, scaling, and latency/throughput optimisation •
Build and maintain training and experimentation infrastructure: job orchestration, compute provisioning, experiment tracking, hyperparameter management, and reproducibility tooling •
Implement observability for ML systems: data quality checks, feature drift detection, model performance monitoring, bias checks, alerting, and incident response workflows •
Build and maintain data pipelines for ingestion, transformation, feature engineering, and export across multiple sources and destinations •
Design and maintain a feature store or feature platform layer: serving consistency, point-in-time correctness, and reuse across teams •
Expose well-governed datasets, features, and APIs that models, pipelines, and downstream consumers can rely on •
Enforce secure data handling and compliance with relevant data protection standards, access controls, and audit requirements •
Requirements
As we are expanding our team, we’re looking for ML Platform Engineer to help us make a real difference in the Fintech industry. Ready to join us and shape the future of payments? Let’s make it happen! About the role:
As an ML Platform / MLOps Engineer , you will design, build, and operate the infrastructure, tooling, and pipelines that make machine learning reliable at scale.
You'll sit at the intersection of data engineering, DevOps, and applied ML - owning the platforms and systems that let data scientists and engineers move from experiment to production safely and repeatably.
Your work will power intelligent products and internal automation across the company, and will help shape how the organisation adopts ML and AI responsibly. What you’ll do: •
Contribute to documentation, platform standards, and continuous improvement of ML engineering processes across teams
Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience) •
Experience with data governance concepts: access control, retention, data classification, auditability, and compliance standards • Model monitoring
Experience building and maintaining agentic applications or LLM-powered tools using frameworks such as LangGraph, LlamaIndex, or the Anthropic/OpenAI Agents SDKs •
Familiarity with MCP (Model Context Protocol) or comparable tool/function-calling protocols for LLM integrations
Apply by filling in the form below and send your CV in English!
Experience
5+ years of Data or ML Engineering experience, with at least 3 years shipping ML systems to production. •
Benefits
Annual salary reviews, promotions and performance bonuses •
Refer a friend bonus as we know that working with friends is fun •
Our mission? It’s simple. Help businesses get paid by taking advantage of modern tech and innovative ideas, so payment challenges are a thing of the past. Pro tip:
Additional details
At myPOS, we’re all about helping businesses grow and get paid.
We make payments simple, smart, and accessible for everyone, but we’re more than just payment solutions - myPOS is a partner in growth.
From free multicurrency accounts to powerful e-commerce tools, we’re here to support business owners of all sizes and everyone out there who dreams of starting their own business.
experience: model registries, experiment tracking (MLflow or Vertex Experiments), pipeline orchestration, and reproducible training runs. •
experience: drift detection, data quality issues, performance degradation, bias checks, and alerting strategies •
Vibrant international team operating in hi-tech environment •
Unlimited access to courses on LinkedIn Learning •
Teambuilding, social activities and networks on a multi-national level Who we are:
Since 2014 we’ve been all about making payments easier and more accessible for businesses of all shapes and sizes.
Whether you’re at the counter, selling online, or on the move, we’ve got businesses covered with smart, accessible and affordable solutions that keep things easy.