Machine Learning Engineer

Contract Machine Learning Engineer – Financial Services (Austin, TX) Duration: 6 months Rate: $110–$130 per hour Location: Austin, Texas (Hybrid – 1 day onsite per week) We are looking for a skilled Machine Learning Engineer to join a leading Financial Services organisation in Austin on a 6-month contract. This role involves working on production-grade ML systems, taking models from development to deployment in a high-volume, regulated environment. Key Responsibilities • Design, build, and deploy machine learning models into production for Financial Services use cases • Collaborate with Data Scientists, Engineers, Product, and Risk teams to deliver end-to-end ML solutions • Build and maintain ML pipelines for training, evaluation, deployment, and ongoing monitoring • Ensure models meet performance, reliability, and regulatory requirements • Apply MLOps best practices, supporting reproducibility, versioning, and model governance • Monitor deployed models for drift and performance, implementing improvements as needed Required Skills & Experience • Commercial experience as a Machine Learning Engineer, ideally in Financial Services, FinTech, or a regulated industry • Strong Python skills with hands-on experience in ML libraries such as TensorFlow, PyTorch, or scikit-learn • Proven experience deploying and supporting ML models in production • Solid understanding of software engineering best practices and cloud platforms (AWS, GCP, or Azure) • Familiarity with regulatory compliance and model explainability requirements Preferred / Nice-to-Have • Experience with fraud detection, credit scoring, risk modelling, AML, or customer analytics • Knowledge of MLOps tooling (MLflow, Kubeflow, Airflow) • Containerisation and orchestration (Docker, Kubernetes) • Exposure to model validation, auditing, and compliance frameworks Contract Details • $110–$130 per hour (contract) • 6-month engagement with potential extension • Hybrid work: 1 day per week onsite in Austin • Immediate or short-notice start • Must be authorised to work in the US