Marc Oppenheimer is a Senior Software Engineer with six years’ experience building production-grade data and ML systems, currently shaping unified recommendation and ML practices at Canonical after impactful work at the BBC. He has delivered high-throughput, low-latency recommender pipelines on GCP—serving 70M weekly requests and cutting costs by £720K/year—while partnering closely with data scientists to productionise models and expose real-time data streams. Comfortable across Apache Beam, Airflow, Kubernetes, Redis and Terraform, Marc focuses on reliable, scalable architectures that lower barriers to experimentation and operationalise ML. He combines a physics MSci background with a pragmatic belief that technical problems are often human problems, and he enjoys translating stakeholder needs into resilient engineering solutions. An experimental thinker, he has a track record of replacing third-party systems with in-house solutions that both improve metrics dramatically and reduce vendor spend.
6 years of coding experience
3 years of employment as a software developer
MSci Physics, Physics, MSci Physics, Physics at University of Birmingham
Contributions:21 reviews, 14 PRs, 48 pushes in 1 year 9 months
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Marc Oppenheimer - Senior Software Engineer at Canonical