Senior Machine Learning Engineer

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.

Job Responsibilities

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

Document methods and decisions to keep models transparent and reproducible

Requirements

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

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), containerised and deployed on Kubernetes or similar

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

Desirable Skills

MLOps practices: model and data versioning, automated retraining, monitoring, and champion/challenger evaluation

Distributed data processing (e.g. Dask, Spark, Apache Arrow/parquet) and handling columnar data at scale

Deeper neural-network / PyTorch experience

Model explainability (e.g. SHAP) and probability calibration

Experience with LLM-based or agentic systems (tool use, orchestration, retrieval)

Familiarity with workflow orchestration and event/stream processing is a plus

Experience in regulated or data-intensive industries, ideally financial services

Familiarity with cloud-based ML infrastructure

Qualifications

Degree in Computer Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience

Experience

4-6+ years in machine learning engineering, or software engineering with a strong ML component

Experience delivering and operating ML models in production

Experience working in cross-functional teams delivering software products

Strong problem-solving skills and a pragmatic, ownership-driven approach to shipping reliable software

Equality Statement

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.

#J-18808-Ljbffr