AI/ML Technical Lead

QUALCO

full-time

Posted on: 9/20/2025

Origin: • 🇬🇷 Greece

✨ AI Apply

Senior

AzureCloudHadoopLinux.NETNoSQLPythonSpark

About the role

Lead the AI/ML stream within the D3E (Data-Driven Decisions Engine) product development team
Define and execute AI/ML technical strategy aligned with product roadmap and business objectives, including GenAI, Cloud, and distributed computing
Architect and oversee end-to-end machine learning lifecycle from ideation to production deployment, ensuring scalability and reliability
Drive the design, development, and deployment of AI and machine learning models and algorithms to enhance D3E's analytical capabilities
Provide technical guidance on GenAI, advanced ML algorithms, model evaluation, optimization techniques, and MLOps best practices
Lead, mentor, and grow a team of AI/ML engineers and data scientists, fostering innovation and continuous learning
Collaborate with software engineers, data scientists, and product managers to deliver integrated AI solutions
Participate in product brainstorming, roadmap, design, prototyping, and development activities with a focus on AI-driven features
Stay current with GenAI/AI/ML research and evaluate their application to financial technology products

Minimum 8+ years of professional experience in machine learning engineering with at least 1 year in technical leadership or team management roles
Proven track record of leading AI/ML projects from conception to production deployment in enterprise environments
Experience managing and mentoring technical teams, with strong leadership and communication skills
Advanced knowledge of machine learning algorithms, GenAI, and model evaluation techniques, interpretability
Experience deploying AI Agents, Agentic Frameworks, information retrieval techniques (RAG, GraphRAG), vector DBs
Extensive experience with Python or C#, .NET framework, and modern source code revision control (Git) for ML model development and deployment (MLOps)
Deep understanding of Cloud and Big data ecosystem (Spark, Hadoop, etc) and their application to ML workloads; Experience with Azure will be considered a plus
Strong understanding of relational DBs and ideally NoSQL/datalakes and their applicability within Data and AI applications
Experience in financial services, fintech, or regulatory compliance environments
Knowledge of Linux systems and command-line tools for ML model deployment
Strong verbal and written communication skills, as well as effective cooperation skills, in both Greek and English.