Solutions Engineer - Physical AI

roofline; Köln; On-site; EUR 75,000 - 110,000; Full time

Benefits offered by this job

Equity for every employee

Flexible schedule / time off

Team events and retreats

Job summary

Roofline is building a Deployment Platform to run AI models on disruptive edge hardware. As a Solutions Engineer, you will make that real for our customers by getting their models running on their hardware, driving proof-of-concepts to adoption, and representing Roofline at conferences.

You will act as technical lead on customer engagements, design and build applications with Roofline’s tools on real use cases, and translate customer needs into concrete product direction while mentoring

Qualifications

• 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).
• Track record of taking AI use cases from vague customer conversations to a working prototype on target hardware.

Responsibilities

• As the technical face of Roofline, you represent us to customers and ecosystem partners at conferences, in technical talks and workshops.
• 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.

Skills

AI experience

Embedded systems

C/C++

Python

Communication skills

Customer engagement

Education

Degree in Computer Science or Electrical Engineering

Tools

PyTorch

ONNX

MLIR

TVM/IREE

Job description

Roofline is building a Deployment Platform to run any AI model on disruptive hardware at the edge. As a Solutions Engineer, you’ll make that real for our customers: getting their models running on their hardware, driving proof-of-concepts to adoption, and representing Roofline at conferences. What you learn in the field shapes what our engineering team builds next.

• The opportunity to grow. Be at the forefront of building and shaping an industry-defining venture. There are plenty of opportunities to learn and evolve.
• The team succeeded. We are building the leading AI compiler team in Europe. Join our future-focused team to contribute to meaningful, disruptive innovations with us.
• The flexibility you need. Whether you need to take extra time off, adjust your schedule, or have other ideas to maximize your productivity, we’ve got your back
• The compensation that rewards. We are looking for world class talent and pay accordingly. We offer equity for every employee since we truly want you to participate in our success.
• The culture you desire. We actively make space to build our culture. We organize dedicated regular events and retreats for the whole team.

• 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.

• 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.