SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.
We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.
At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.
The SandboxAQ AI Generation Engine team's mission is to accelerate SandboxAQ’s mission of “Deep Impact at Scale," with a focus on quantitative AI and rapid prototyping. More specifically, the SAIGE team aims to:
Our team operates on the following principles: Prototype with Velocity, Explore Boldly, Fail Smart, Learn Fast, Look Forward, and Share Knowledge.
SandboxAQ is a pacesetter for AI LQM product development, and this role will drive the technical execution of those efforts. You will be responsible for the technical design, architecture, and development of LQM prototypes and products in line with the AI strategy. You have deep technical expertise and are capable of contributing in a hands-on way to research and development as well as planning and mentoring / managing a team of engineers.
Technical Ownership:
Prototyping and Development:
Innovation:
The US base salary range for this full-time position is expected to be $263K - $368K per year. Our salary ranges are determined by role and level. Within the range, individual pay is determined by factors including job-related skills, experience, and relevant education or training. This role may be eligible for annual discretionary bonuses and equity.
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