Do you get excited about working alongside engineers and scientists on problems that will have a significant and lasting impact for Amazon customers? Are you thrilled about working in a startup-like environment? Search no more! We have an opening for a Sr. Product Manager (Tech) in Berlin.

The Content Systems Science and Engineering team supports a wide range of initiatives across Amazon in the domains of content understanding (e.g., computer vision), image rendering (e.g., compression technologies), and asset optimization (e.g., image ingestion).

Your work will impact the shopping experience for millions of Amazon customers every day. Your ideas allow a fast path to production at scale and help us reshape the way we think about images at Amazon.

Key job responsibilities
- You work effectively with customers and stakeholders to deliver complex features successfully.
- You help the team navigate business processes for experiments and feature launches.
- You understand the science and technology behind your team's offerings and help partners deliver value for customers more quickly.
- You define the strategic vision together with the team, establish a roadmap, and support the team and stakeholders to successfully deliver on that vision.
- You help the team make crisp decisions about what projects move forward and in what priority order.
- You influence scientific and technical priorities as well as business strategy through data-driven contributions on a continuous basis.
- You communicate ideas, project updates, and blockers to a wide range of audiences (e.g., tech and non-tech stakeholders).
- You foster a constructive dialogue, harmonize discordant views, and lead the resolution of contentious issues.
- You simplify: You judiciously add, refine, and remove features and understand how to continuously deliver impact.
- You demonstrate creativity and enthusiasm when facing constraints or setbacks.
- You participate in the hiring process and mentor others.


About the team
The Content Systems Science and Engineering team is mixed: scientists work closely together with engineers. Examples of the domains we tackle include, but are not limited to: 1) optimizing image processing in the backend (e.g., compression and scaling algorithms), 2) optimizing image rendering in the front-end (e.g., modern image file formats), and 3) extract and process foundational image data with the help of computer vision (e.g., vision transformer backbones).

The team cares about everyone's success and well-being (e.g., find happiness in life).