<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p><strong>Senior Machine Learning Engineer</strong></p><p>📍 Vienna, Austria</p><p><br/></p><p>Prototypes are exciting. Production is where things get real.</p><p><br/></p><p>At SmartStream, we help the world's largest financial institutions reconcile billions of transactions every month. We're looking for a Senior Machine Learning Engineer to join our Vienna team and take our ML and AI capabilities from notebook to production — powering transaction matching, reconciliation, and exception handling at genuine scale.</p><p><br/></p><p><strong>What you'll do</strong></p><p>You'll own ML services end to end: shipping them, hardening them, and keeping them accurate and reliable long after launch. Working alongside data scientists, software engineers, product managers, and domain experts, you'll turn messy real-world reconciliation problems into dependable software.</p><p><br/></p><p>Day to day, you'll:</p><ul><li>Develop, deploy, and maintain machine learning models and services — and keep the existing ones performant and robust</li><li>Translate research artefacts and prototypes into production-grade systems: hardening code, adding tests and observability, owning deployment, scaling, and lifecycle management</li><li>Own model serving, monitoring, drift detection, and retraining in production</li><li>Engineer and evaluate features on real financial datasets, and calibrate and validate models for reliable behaviour</li><li>Collaborate closely with engineering and data science on the surrounding data and matching platform</li><li>Document methods and decisions to keep models transparent and reproducible</li></ul><p><br/></p><p><strong>The scope</strong></p><p>You'll work across the full spectrum of applied AI — from classical ML (supervised, unsupervised, and deep learning) through to agentic AI built on large language models, tool use, and multi-step reasoning. This is a hands-on engineering role: the emphasis is on productionising, not paper-</p><p>writing.</p><p><br/></p><p><strong>What we're looking for</strong></p><p>Core skills:</p><ul><li>Strong software engineering in Python: clean, typed, well-tested code, version control, and CI/CD</li><li>Strong proficiency with the scientific Python stack (NumPy, Pandas, scikit-learn, PyTorch) and a solid, practical grasp of ML, statistics, and model evaluation</li><li>Experience taking ML models into production and operating them there (serving, monitoring, retraining) — not just building them in notebooks</li><li>Experience building and running production services and APIs (e.g. FastAPI or Flask), containerised and deployed on Kubernetes or similar</li><li>Feature engineering on structured/tabular data, and sound model evaluation and validation</li><li>Ability to work with large datasets and build reliable data pipelines</li><li>Clear communication with technical and business stakeholders</li></ul><p><br/></p><p>Nice to have:</p><ul><li>MLOps practices: model and data versioning, automated retraining, monitoring, and champion/challenger evaluation</li><li>Distributed data processing (Dask, Spark, Apache Arrow/parquet) and handling columnar data at scale</li><li>Deeper neural-network / PyTorch experience</li><li>Model explainability (e.g. SHAP) and probability calibration</li><li>LLM-based or agentic systems (tool use, orchestration, retrieval)</li><li>Workflow orchestration and event/stream processing</li><li>Experience in regulated or data-intensive industries, ideally financial services</li><li>Cloud-based ML infrastructure</li></ul><p><br/></p><p><strong>Experience</strong></p><ul><li>Experience in machine learning engineering, or software engineering with a strong ML component</li><li>Delivering and operating ML models in production</li><li>Working in cross-functional teams delivering software products</li><li>Strong problem-solving skills and a pragmatic, ownership-driven approach to shipping reliable software</li></ul><p><br/></p><p><strong>Qualifications</strong></p><p>Degree in Computer Science, Engineering, Statistics, Mathematics, or a related field — or equivalent practical experience.</p><p><br/></p><p><strong>Why SmartStream</strong></p><p>We've spent 40+ years solving post-trade problems for tier-one banks, asset managers, and fintechs. Our platforms process over 10 billion transactions a month, and our AI work is core to where the business is going — not a side project.</p><p>Ready to build ML that actually runs? Apply below, or message me directly.</p><p><br/></p><p><em>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.</em></p><p>#MachineLearning #MLOps #Hiring #Vienna #Fintech #PythonJobs #AICareers</p> </div>