About the company
Our client is a technology company.
The role
Raydar is recruiting for this role on behalf of our client. Own the full-stack product and the AI engineering behind it, taking systems from prototype to production for business users. You will work as a hands-on generalist with a lean toward backend work, partnering closely with the founders and a very small engineering group. The role also covers internal tooling, quality measurement and helping shape the team.
What you'll do
- Build and own backend services, data storage, APIs and an application layer, moving them from prototype to production.
- Integrate multi-step AI reasoning workflows into real customer operating procedures and field processes.
- Co-own evaluation tooling and a feedback loop, designing evaluations with limited data and tracking failure modes to improve model quality each release.
- Build internal tooling and automate company workflows with AI, making build-versus-buy decisions.
- Contribute to go-to-market planning by helping choose which customer segments to pursue next.
- Help recruit and onboard additional engineers as the team grows.
Requirements
What we're looking for
- Early-career engineer, roughly one to three years in, who has put AI-driven or multimodal products in front of real users.
- Ability to own a real-time media pipeline end to end, with depth in low-latency streaming over unreliable networks, media capture, or low-latency model serving.
- A record of early-stage startup work that reached production, or time spent in a demanding, high-ownership engineering culture.
- Backend-leaning full-stack skills, having built databases, APIs and app layers on a modern cloud stack.
- Experience connecting physical devices to software, such as wearables, cameras, robotics, IoT or drones.
- Comfort working close to the hardware in a systems language, including profiling and working within memory and power limits.
- Strong computer science or engineering background, or an equivalent record of shipping.
- Hungry, scrappy and independent, with active use of the latest AI tools.
- Willingness to work on-site five days per week.
Bonus points
- Computer vision, wearable or AR product experience.
- Edge or on-device inference deployment.
- On-prem or air-gapped deployment in high-security environments.
- Device and firmware fluency, including embedded Linux or device SDKs.
- Founder background or exposure to industrial domains.
- Relevant big-company experience on a directly related team, paired with a builder track record.
Benefits
Compensation and benefits
- Base salary: USD 170,000 to 230,000 per year
- Equity
Location and work model
- San Francisco, CA, United States
- On-site, 5 days per week
- Full-time
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- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
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- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
