ML Platform Engineer at myPOS UK

Varna, Varna, Bulgaria -

Full Time

Start Date

Immediate

Expiry Date

08 Sep, 26

Salary

0.0

Posted On

10 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, MLOps, CI/CD, Terraform, Docker, GCP, Airflow, Spark, BigQuery, Model Serving, Feature Stores, MLflow, Vertex AI, Data Pipelines, Observability

Industry

Financial Services

Description

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. 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: 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 Contribute to documentation, platform standards, and continuous improvement of ML engineering processes across teams This role is perfect for you if you have: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field (or equivalent practical experience) 5+ years of Data or ML Engineering experience, with at least 3 years shipping ML systems to production. Strong Python skills (typed code, async, testing) and solid SQL fluency. Hands-on MLOps experience: model registries, experiment tracking (MLflow or Vertex Experiments), pipeline orchestration, and reproducible training runs. Strong DevOps fundamentals: CI/CD (GitHub Actions, Cloud Build, or similar), IaC (Terraform), containerization (Docker). Familiarity with at least one major cloud provider (GCP, AWS, Azure) and deploying data solutions in the cloud Experience building and maintaining data pipelines with orchestrators (Airflow/Composer, Dagster) and distributed engines (Spark, BigQuery) Strong troubleshooting mindset: ability to debug issues across data, infra, pipelines, and deployments Collaborative mindset and clear communication across engineering, analytics, and business stakeholders Nice to have: Strong GCP experience and ecosystem knowledge: Vertex AI (Model Garden, Pipelines, Endpoints, Experiments, Monitoring), BigQuery, Composer, Dataproc, Cloud Run, Dataplex, Cloud Storage Experience with data governance concepts: access control, retention, data classification, auditability, and compliance standards Model monitoring experience: drift detection, data quality issues, performance degradation, bias checks, and alerting strategies 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 Why you should join myPOS: Vibrant international team operating in hi-tech environment Annual salary reviews, promotions and performance bonuses myPOS Academy for upskilling and training Unlimited access to courses on LinkedIn Learning Annual individual training and development budget Refer a friend bonus as we know that working with friends is fun Teambuilding, social activities and networks on a multi-national level What we offer: Excellent compensation package 25 days annual paid leave (+1 day per year up to 30) Full “Luxury” package health insurance including dental care and optical glasses Meal vouchers of 102.26 EUR per month Fully covered Multisport card Fully covered public transport pass for Sofia Free coffee, snacks and drinks at the office 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. 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: Take it easy about meeting every requirement - this job description is just that, a job description! Even if you don’t tick every box, we want you to apply anyway! This is your chance to grow, learn, and build your career with us. We value potential over perfection, and we are all about mutual growth! Apply by filling in the form below and send your CV in English! myPOS is committed to providing equal employment opportunities. All qualified candidates will be considered for employment without discrimination based on age, ancestry, color, marital status, national origin, physical or mental disability, medical condition, veteran status, race, religion, sex, sexual orientation, gender identity or expression, or any other characteristic protected by applicable laws, regulations, and ordinances. Your application will be confidentially reviewed in line with the General Data Protection Regulation (GDPR). Personal information will be used solely for the job application and will be stored for a period needed by the application process. Only short-listed candidates will be contacted. Good luck!

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Responsibilities

Design and operate the infrastructure, tooling, and pipelines required to scale machine learning models from experiment to production. This includes building MLOps automation, managing model serving infrastructure, and implementing observability for ML systems.