Teams at DeepL

Lead product-led growth for DeepL Translate with an initial focus on media translation. Define high-value use cases, build growth loops, own PQL definition and instrumentation, drive adoption across web, extensions, apps and APIs, coordinate with Sales/Marketing/Pricing, and measure product usage impact on pipeline, revenue and retention.

Own the reliability, capacity, cost efficiency, and lifecycle of DeepL’s hybrid CPU and GPU infrastructure across AWS and on-premises environments. Design and operate production Kubernetes clusters, establish infrastructure-as-code and platform standards, improve observability and security, lead incident response, and drive root-cause remediation. The role also shapes platform architecture, advances hybrid cloud integration, mentors engineers, builds cross-team consensus, and supports sustainable on-call operations.

Lead the Production Inference team of research scientists and ML engineers. Own people development, technical direction, research and development roadmaps, architecture decisions, and model-serving reliability, efficiency, latency, and cost performance. Partner with research, infrastructure, product, and commercial stakeholders; guide production deployment and lifecycle improvements; and recruit technical talent. The role emphasizes leadership and technical reviews rather than hands-on coding.