François Kawala is a seasoned machine learning engineer and team leader with 14 years of experience building and shipping ML systems across startups, mid-size companies, and large corporations. He combines hands-on expertise in Python and Scala with production-grade ML-Ops and edge/data-engineering tooling (Kubernetes/Kubeflow, Prometheus, Elasticsearch, Grafana, Flux CD, GitLab CI) to turn models into reliable services. As a former lead at Infomaniak and staff engineer at Grid Dynamics, he has driven company-wide data mesh and on-prem ML stack initiatives while mentoring engineers to grow autonomy and skill. His academic background—a PhD in AI—underpins a rigorous approach to problem framing and forecasting in social networks, a thread visible from early research to applied product features like document classification and miner detection. Colleagues praise his clear, empathetic communication and pragmatic focus on projects with strong business impact. He is curious and adaptable, recently transitioning to Apple to continue scaling production ML in complex environments.
14 years of coding experience
11 years of employment as a software developer
doctor philosophiæ (PhD) Artificial Intelligence, doctor philosophiæ (PhD) Artificial Intelligence at Université Grenoble Alpes
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