MLOps Engineer responsible for managing PyTorch - based training and inference workloads at Menlo HQ. Building and maintaining robust infrastructure for AI models and optimization processes.
About the role
- Machine Learning Engineer developing machine learning models for a leading fintech company in Greece. Collaborating with engineering and data teams to enhance decision-making across the financial ecosystem.
Responsibilities
- Design, develop, and maintain machine learning models and AI-driven solutions supporting next-generation fintech products.
- Collaborate with software engineers, data scientists, analysts, and product teams to integrate machine learning capabilities into production systems.
- Contribute to ML pipelines covering data preparation, model training, evaluation, and inference workflows.
- Support deployment and monitoring of machine learning models using modern MLOps practices.
- Participate in product design discussions, experimentation, and prototyping, focusing on AI-powered features.
- Evaluate emerging machine learning and generative AI frameworks to assess their potential applicability in production.
- Document models, experiments, datasets, and operational processes to ensure maintainability, transparency, and auditability.
- Contribute to best practices in machine learning lifecycle management, supporting reliable model deployment and continuous improvement.
Requirements
- 4–6 years of experience in machine learning engineering or applied data science roles on algorithmic product design.
- Hands-on experience developing and deploying machine learning models in production environments.
- Strong programming skills in Python, with experience using version control systems such as Git.
- Solid understanding of machine learning algorithms, model evaluation techniques, and interpretability concepts.
- Exposure to Generative AI frameworks or modern ML ecosystems is a plus.
- Familiarity with CI/CD pipelines, Docker, Kubernetes, and modern MLOps practices.
- Understanding of cloud services and ML workloads, with Azure experience considered a plus.
- Knowledge of relational databases, and ideally exposure to NoSQL or data lake systems used in AI applications.
- Nice Additions
- Experience in financial services, fintech, or regulatory compliance environments is an advantage.
- Familiarity with Linux systems and command-line tools for ML model deployment and experimentation.
- Strong collaboration and communication skills in English; Greek is considered an advantage.
Benefits
- Competitive salary package 3200 - 3500 gross euros monthly
- Meal benefits: Ticket restaurant (120 euros x 12) and annual bonus programs.
- Private health insurance and onsite occupational doctor
- Cutting-edge IT equipment, mobile, and data plan.
- Modern facilities, free coffee, beverages, and indoor parking.
- Onsite gym, wellness facilities, and ping pong room.
- Flexible work arrangements currently on 50% - 50% ratio working from home
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