Professional Summary
Machine Learning Engineer with 5+ years of experience designing scalable ML systems and deploying data-driven features. Specialises in productionising complex models, improving CI/CD pipelines, and maintaining high service reliability. Currently leading ML infrastructure at Turing while mentoring junior engineers.
Skills
- Machine Learning
- Python
- Tensorflow
- Pytorch
- Communication
- Cloud Computing
- MLOps
- Data Engineering
Experience
ML Engineer — Turing
- Architected feature extraction pipelines that reduced model training latency by 40%.
- Implemented A/B testing framework serving 200k monthly users with automated guardrails.
- Improved CI/CD cadence by 50% through containerised workflows and pre-merge validation.
- Optimised Hyperparameter tuning infrastructure, cutting experiment cycle times from weeks to days.
- Mentor three junior data scientists on deployment best practices and observability.
Systems Analyst — Swish Analytics
- Designed real-time dashboards serving 50+ clients, increasing upsell opportunities by 25%.
- Automated data quality checks that reduced reporting errors by 80% across three product lines.
- Collaborated with engineering to migrate analytics pipelines from on-prem Hadoop to AWS.
- Authored documentation that improved cross-team SLAs on data availability and reliability.
- Led monthly data clinics to elevate analytics literacy across business teams.
Education
M.S. Computer Science
Carnegie Mellon University
Certifications
- AWS Certified Machine Learning - Specialty
- TensorFlow Developer Certificate