Hybrid Machine Learning, AI Architect

at UMO

• Job title: Machine Learning, AI Architect
• Job type: Full Time
• Experience level: Senior, Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Docker, Google Cloud Platform, Kubernetes, Python, PyTorch, Tensorflow
• Location requirements: Hybrid, Lisbon, Portugal

About the role

• ML AI Architect designing end-to-end AI architectures for fintech platform. Leading AI innovation and ensuring secure, scalable infrastructure for financial services.

Responsibilities

• Architecting the Intelligence Layer: Design end-to-end AI/ML architectures, including RAG pipelines, agentic workflows, and real-time decisioning systems tailored to financial services.
• Infrastructure Oversight: Select, govern, and continuously evolve our AI stack (LLM providers, vector databases, orchestration frameworks, and MLOps tooling).
• Engineering Standards & Observability: Establish engineering excellence for AI, including automated testing frameworks, model evaluation pipelines, drift detection, bias monitoring, and CI/CD processes tailored for machine learning in regulated environments.
• Innovation at Production Depth: Partner with the Head of AI Innovation to translate AI product hypotheses into technically viable architectures.
• Trust, Guardrails & Runtime Governance: Embed explainability, auditability, and human-in-the-loop mechanisms into all AI systems.

Requirements

• Proven Expertise: 8+ years in software engineering, with at least 3 years in an Architect or Lead role focused on AI/ML.
• FinTech/Crypto Background: Strong understanding of financial data, transaction patterns, and the unique security requirements of the FinTech or Crypto space.
• Technical Mastery: Deep proficiency in Python and modern AI frameworks (PyTorch, TensorFlow, LangChain, or LlamaIndex).
• Production Experience: A track record of deploying large-scale, production-grade AI systems (not just experimental models).
• Cloud Native: Extensive experience with AWS, Azure, or GCP AI services and containerization (Kubernetes/Docker).
• Communication: Fluent English and the ability to articulate complex technical concepts to non-technical stakeholders.
• Startup Mindset: Ability to thrive in a fast-paced, stealth-mode environment where adaptability is key.

Benefits

• Compensation: A highly competitive salary package that recognizes your expertise and contribution.
• Modern Work Culture: Embrace a remote-first environment with flexible working hours, designed to support your work-life harmony.
• Generous Time Off: Annual Leave - 24 days, dedicated paid sick leave, and Public Holidays.
• Professional Evolution: Grow your skills with a dedicated learning budget and clear pathways for accelerated career development.