Your Responsibilities:
- Design and deliver scalable AI and machine learning solutions across underwriting, risk, and operations
- Own the end-to-end ML lifecycle, from feature engineering to deployment and monitoring
- Build and maintain data pipelines and production workflows using Python, TensorFlow, PyTorch, scikit-learn, AWS (S3, Lambda, SageMaker, Step Functions, Bedrock), Snowflake, and Dataiku
- Apply MLOps best practices, including CI/CD, automated testing, model versioning, and observability
- Define deployment standards and track model performance in production
- Contribute to GenAI/LLM initiatives and reusable solution designs
- Ensure compliance with governance, risk, and responsible AI standards
- Collaborate with cross-functional teams to translate business needs into practical AI solutions
Your Experience:
- 3+ years experience in machine learning, data science, and software development
- Proficient in Python and/or R
- Experience with cloud platforms (e.g. AWS), Linux, and containerised environments
- Familiar with modern AI/GenAI approaches (e.g. RAG)
- Good understanding of data modelling, governance, and security
- Experience with Agile, DevSecOps/DataOps, and testing in production environments
- Strong problem-solving skills with a proactive, collaborative mindset
If interested in learning more, please apply directly or email me - [email protected]
