Senior Machine Learning Engineer
Role details
Job location
Tech stack
Job description
We are looking for a Senior Machine Learning Engineer to conduct research and develop advanced AI solutions that enhance SmartStream's financial data processing and reconciliation platforms. In this role, you will work with large and complex financial transaction datasets to design and evaluate models supporting tasks such as transaction matching, exception management, intelligent automation of operational workflows, and many other data-driven capabilities.
The position has a strong research and experimentation component. In addition to applying established machine learning methods, you will explore and prototype new approaches, including agentic AI solutions that can assist users in navigating and automating complex reconciliation processes.
Working closely with engineers, product managers, and domain experts, you will translate real-world reconciliation challenges into robust machine learning approaches and help shape how emerging AI techniques can be applied within our products., * Design, train, and evaluate machine learning models for product and operational use cases
- Explore and analyze datasets to identify patterns, insights, and modelling opportunities
- Collaborate with software engineers to deploy and maintain models in production
- Define model evaluation, monitoring, and retraining strategies
- Contribute to experimentation, prototyping, and research on new modelling approaches
- Document methods, assumptions, and results to ensure transparency and reproducibility
Requirements
Do you have a Master's degree?, * Strong proficiency in Python and common data science libraries (e.g. NumPy, Pandas, scikit-learn, PyTorch)
- Solid understanding of machine learning, statistics, and data analysis methods
- Familiarity with agentic AI systems and modern AI architectures (e.g. LLM-based applications, tool-using agents, orchestration frameworks) and the ability to apply them when designing and building practical software solution
- Experience developing and evaluating predictive models in production environments
- Ability to work with large datasets and build reliable data pipelines
- Experience communicating analytical findings clearly to technical and business stakeholders
Desirable Skills
- Experience with deep learning, reinforcement learning, or generative AI methods
- Familiarity with MLOps practices such as model monitoring, versioning, and automated retraining
- Experience with distributed data processing frameworks or cloud-based ML platforms
- Knowledge of vector databases, retrieval methods, or LLM-based systems
- Experience in regulated or data-intensive industries, * Degree in Computer Science, Statistics, Mathematics, Engineering, or a related field
- Strong problem-solving skills and curiosity about emerging AI and data science methods
Experience
- 4-6+ years of experience in data science or machine learning roles
- Demonstrated experience delivering machine learning models in production
- Experience working in cross-functional teams delivering data-driven products