Compensation
$152,000-$190,000Description
The next frontier for AI is the physical world. At Scale, we're pioneering this shift, moving artificial intelligence from digital spaces into robotics and autonomous systems. Our Autonomous Driving (AD) and Robotics team is building the data engine and infrastructure that powers L3/L4 autonomy and complex robotic manipulation. We are looking for a pivotal Solutions Engineer to join this team..
As a Solutions Engineer, you'll be a trusted technical partner to the world's most innovative Foundation Model builders and renowned robotics companies (from Humanoids to Robotaxis). You will partner closely with Product, Sales, and ML Engineers to guide prospective customers through the pre-sales process, delivering customized demos and Proof of Concepts that secure the "technical win.
You’ll help customers bridge the gap between simulation (Digital Twins) and real-world deployment by defining technical requirements for multi-modal real-world data pipelines (LiDAR, Radar, Camera, and IMU). You'll develop actionable Statements of Work and collaborate with the delivery team on high-fidelity ground truth implementation. Your expert knowledge of Scale's products will allow you to design creative, impactful solutions.
This is a critical role that directly influences multi-million dollar contracts and initiatives. You'll travel globally to conduct on-site technical workshops and scope new projects, while also leading demos and pilots for new prospects. You'll be part of a tight-knit, specialized team, influencing a rapidly growing business that is expanding into new product areas.
In this role, you will:
- Partner with Scale Account Executives and Engagement Managers to deliver new customer pilots and grow technical relationships with existing clients.
- Work with Product Engineering and Product Management to influence our product roadmap based on your frontline insights.
- Become a domain expert in next-generation Robotics and physical AI (e.g. VLMs, VLAs, World Models)
- Develop technical domain expertise in areas of 2D and 3D imaging and annotation, multi-sensor fusion and calibration, GPS/INS navigation systems, computer vision and other autonomy-adjacent concepts
- Be accountable for the technical customer experience and commercial growth, expanding relationships and use cases with existing customers.
- Collaborate with highly technical engineers at our customer sites to ensure satisfaction with our data, software platforms, and workflows.
- Design and develop playbooks, demos, and other tools to ensure efficient and successful pilots and customer expansions.
- Pioneer the development of a global Robotics Data Marketplace, actively seeking out and engaging with key international partners to build a comprehensive data ecosystem.
- Evangelize Scale by interacting with customers at major industry events and academic conferences.
You have:
- A strong engineering background, preferably in Robotics, Mechatronics, Computer Science, Mathematics, or other Engineering fields.
- 3+ years of experience developing with Python, C++, Java, and/or other scripting languages.
- Hands-on experience in Autonomous Driving, Robotics or Physical AI
- Exceptional project management and interpersonal skills, strong attention to detail, and a strong sense of ownership.
- The presentation skills and technical credibility to speak confidently with a variety of stakeholders, from executives to front-line engineers.
- A high level of comfort communicating effectively across internal and external organizations.
- Regular travel within the Bay Area.
- International travel approximately once every two months.
- Intellectual curiosity, empathy, and the ability to operate with a high degree of autonomy.
Bonus points if you have:
- Prior sales, solutions engineering, or partnership experience with a track record of successfully achieving quota.
- Ideally would have experience selling complex technical solutions to enterprises with deal sizes of $500K to $5M+.
*This role can be based in San Francisco, New York, Detroit or Denver.
Stack
- Posted
- Jun 30, 2026
- Last seen
- Jun 30, 2026
- First seen
- Jun 30, 2026


