Top Artificial Intelligence Jobs

As a Pre-Sales Solutions Engineer, you'll partner with the sales team to provide technical expertise, build Proofs of Concept, and ensure successful customer transitions while collaborating with product teams.

The Solutions Engineer will demonstrate AI-powered solutions to prospects, conduct technical discovery, and enhance customer engagement. Responsibilities include delivering demos, translating pain points, and collaborating with Product and Marketing teams.

The role involves designing machine learning systems, optimizing real-time data processing, and building large-scale pipelines for fraud detection.

Use Modus' AI platform to complete audit workpapers end-to-end at high speed, pull ready work from the practice management system, ensure quality with reviewers, and provide product feedback to improve the tools.

As a Software Engineer, you will develop and maintain features using AI-assisted tools, collaborate with teams, and enhance software solutions for better user insights.

Develop multi-DOF robotic systems for surgical applications, ensuring compliance with FDA guidelines and leading engineering teams. Collaborate with various departments to solve interdisciplinary challenges.

As Head of Growth & Marketing, you will define and execute the go-to-market strategy, drive user acquisition, create content, engage developer communities, and lead product marketing efforts while collaborating with teams and influencing growth initiatives.

As Director of Sales, lead the SDR, SMB, and Mid-Market teams to drive revenue and build scalable sales processes. Manage recruitment, coaching, and performance analysis while fostering a culture of excellence.

As a Solutions Engineer, you will lead technical pre-sales, engage customers, provide product expertise, and support successful adoption of Statsig's experimentation platform.

Drive institutional liquidity and TVL by sourcing, pitching, and onboarding market makers, CEX VIPs, prime brokers, and large allocators. Build strategic partnerships, structure and close liquidity incentives, and collaborate with product/tokenomics to design institutional yield strategies tied to TVL KPIs.