Job
- Level
- Senior
- Job Field
- Data, Application
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Vienna
- Working Model
- Onsite
Job Summary
In this role, you will develop powerful machine learning systems for processing and reconciling financial data, transforming prototypes into production-ready solutions, and operating them in a robust, scalable environment.
Job Technologies
Your role in the team
- We are looking for a Senior Machine Learning Engineer to build, ship, and operate the machine learning and AI solutions at the core of SmartStream's financial data processing and reconciliation platforms.
- Working with our data scientists, you will turn prototypes into cohesive, production-ready systems, using large and complex financial transaction datasets to power capabilities such as transaction matching, reconciliation, and exception handling.
- You will work across the full spectrum of applied AI, from classical machine learning (supervised, unsupervised, and deep learning) to agentic AI solutions built on large language models, tool use, and multi-step reasoning.
- This is a hands-on engineering role.
- The emphasis is on productionising: turning models into robust, well-tested, observable services and keeping them accurate and reliable in production.
- You will own existing ML services end to end and evolve them, working closely with software engineers, data scientists, product managers, and domain experts to turn real-world reconciliation challenges into dependable software.
- Develop, deploy, and maintain machine learning models and services, and keep existing ones performant and robust.
- Translate research artefacts and prototypes into production-grade ML systems: hardening code, adding tests and observability, and owning deployment, scaling, and lifecycle management.
- Own model serving, monitoring, drift detection, and retraining in production.
- Engineer and evaluate features on real financial datasets, and calibrate and validate models for reliable behaviour.
- Collaborate with software engineers and data scientists on the surrounding data and matching platform.
- Dokumentiere Methoden und Entscheidungen, um Modelle transparent und reproduzierbar zu halten.
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Our expectations of you
Education
- Degree in Computer Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience.
Qualifications
- Strong software engineering in Python: clean, typed, well-tested code, version control, and CI/CD.
- Strong proficiency with the scientific Python stack (NumPy, Pandas, scikit-learn, PyTorch) and a solid, practical grasp of machine learning, statistics, and model evaluation.
- Feature engineering on structured/tabular data, and sound model evaluation and validation.
- Ability to work with large datasets and build reliable data pipelines.
- Clear communication with technical and business stakeholders.
- Strong problem-solving skills and a pragmatic, ownership-driven approach to shipping reliable software.
Experience
- Experience taking ML models into production and operating them there (serving, monitoring, retraining), not just building them in notebooks.
- Experience building and running production services and APIs (e.g., FastAPI or Flask), containerized and deployed on Kubernetes or similar.
- 4-6+ Jahre in Machine Learning Engineering oder Software Engineering mit einem starken ML-Komponent.
- Experience delivering and operating ML models in production.
- Experience working in cross-functional teams delivering software products.
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What we offer
- Smartstream is an equal opportunities employer.
- We are committed to promoting equality of opportunity and following practices which are free from unfair and unlawful discrimination.
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Benefits
Work-Life-Integration
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Topics You Will Work On
Job Locations
About Your Employer
SmartStream Technologies GmbH
Wien
We are a global software and service provider, active in the financial services sector. We provide support to over 1,500 customers worldwide, including 70 of the top 100 banks.
Description
- Founding Year
- 2000
- Company Type
- Established Company
- Working Model
- Onsite
- Industry
- Internet, IT, Telecommunication
Employer reviews
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