REMOTE - MLOps Engineer

About the Role

We are seeking a skilled MLOps Engineer to join our team working on cutting-edge real-time financial market systems. This role bridges the gap between data science and IT operations, ensuring seamless deployment and monitoring of machine learning models that generate actionable trading signals and insights. You’ll be instrumental in integrating AI/ML modules into high-performance environments, including platforms like PDS, ION, and S2BX.

Key Responsibilities

* Automate and streamline the lifecycle of data science products—from experimentation to deployment and monitoring.

* Design and maintain robust MLOps pipelines for reproducible experimentation, model versioning, and automated deployment.

* Refactor, optimise, and package data science code for production use in real-time systems.

* Build integrations with financial market platforms to publish ML-generated signals and analytics.

* Monitor model performance and ensure reliability in live trading environments.

* Provide guidance on MLOps best practices to data scientists and engineering teams.

Requirements

* Proven experience deploying supervised ML models in on-prem or hybrid environments.

* Strong proficiency in Python and core ML libraries: NumPy, pandas, scikit-learn, TensorFlow, PyTorch, Keras.

* Hands-on experience with MLOps platforms such as MLFlow, Databricks, or similar.

* Solid understanding of Linux systems (RedHat preferred) and version control tools (Git).

* Experience with containerisation (Docker, Podman) and CI/CD pipelines (especially Azure DevOps).

* Strong problem-solving skills and eagerness to learn new technologies.

Nice to Have

* Experience with data modeling and RDBMS (PostgreSQL preferred).

* Familiarity with Airflow or other orchestration tools.

* Exposure to distributed computing frameworks (Hadoop, Spark/PySpark).

* Understanding of financial market