Solutions Engineer – Physical AI

• As the technical face of Roofline, you represent us to customers and ecosystem partners, at conferences, in technical talks and workshops. You’ll be the person our sales team brings in when the conversation gets technical.
• Act as technical lead on customer engagements: define the technical approach, plan and coordinate the day-to-day work of the engineers assigned to your project, and own delivery from proof-of-concept to adoption.
• Design and build applications with Roofline’s tools on real customer use cases. Support where it counts: pair with customer engineers, fix integration issues, and get their models running on their target hardware.
• Own the technical strategy of the sales cycle and handle our strategic engagement with customers. Help to build and drive proof-of-concepts, and deliver benchmarks and evaluations (latency, throughput, power, memory footprint) that turn interest into adoption.
• Shape our developer-facing tools to deliver the best possible user experience. Translate customer needs into a technical direction and develop concrete product proposals, working with our engineers to get them built.
• Raise the level of the team around you. Mentor engineers and make our technical go-to-market strategy scalable.

Your profile

• Several years hands-on experience in AI and embedded systems, including experience working with customers and partners.
• Degree in Computer Science, Electrical Engineering, or related fields.
• Strong C/C++, Python skills
• Familiarity with ML frameworks and compiler stacks (PyTorch, ONNX, MLIR, TVM/IREE or similar)
• A track record of taking AI use cases from a vague customer conversation to a working prototype on target hardware. Using model optimization and quantization, deployment through real toolchains and runtimes, and debugging the cases where accuracy or latency doesn't match the datasheet.
• Strong communication and presentation skills, and at ease in front of technical customers, at the whiteboard or on a conference stage.
• Demonstrated technical influence beyond your own deliverables. Have product changes you argued for and got shipped, engineers you've mentored, or practices a team adopted because you established them.
• Ambition and curiosity to solve complex problems, a strong mindset to take ownership and drive our solutions forwards, and a collaborative attitude to foster our culture.

Nice to haves:

• Several years of industry experience building AI models, e.g. in automotive, robotics, vision, or language.
• Experience working with embedded targets or compiler infrastructure, e.g., LLVM.
• Business development and sales experience.

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Source: Statistisches Bundesamt (Destatis), table; dl-de/by-2-0; StarIn's calculation