Top Artificial Intelligence Jobs

Lead Sidetrade Pay as a global embedded B2B payments business across enterprise, SMB, and mid-market customers. Own product vision, roadmap, monetization, pricing, payment partners, adoption, risk, compliance, revenue, and P&L performance. Build payments and product teams, embed payment experiences into Order-to-Cash workflows, expand into embedded finance, and align Engineering, Sales, Customer Success, Legal, Finance, executives, and external partners across multiple regions.

Design, develop, and deploy scalable backend systems and microservices for AI solutions. Collaborate cross-functionally to ship features, optimize application performance, resolve bottlenecks and bugs, and maintain code quality, organization, and automation. The role contributes to early-stage product development and helps shape the company’s technical direction.

Develop and integrate secure AI server platform firmware for customer systems. Responsibilities include server bring-up, peripheral communication over low-level protocols, BMC software development, Linux kernel troubleshooting, secure boot and root-of-trust implementation, and platform integration across NVIDIA, Intel, and AMD architectures. The role also provides technical customer guidance, resolves complex integration issues, and supports custom hardware, embedded systems, microcontrollers, FPGAs, and ARM-based platforms.

Develop and deploy computer vision modules and machine learning models within AI pipelines. Integrate models with data and software engineering teams, support prototypes, automate data pipelines, build internal tooling, and monitor production performance. The role also involves optimization, infrastructure and security support, staying current with computer vision advancements, and collaborating cross-functionally.

Support go-to-market strategy and execution across inbound and outbound channels: define ICPs, join user calls, create Excel demo videos, run outreach using Clay/HeyReach/Instantly, post and measure performance on social platforms, and optimize funnel metrics (visits, conversion, retention, referral).

Develop and optimize high-fidelity Roblox experiences using Luau, Roblox Studio, and advanced platform services. Build gameplay systems, character controllers, AI behavior, UI/UX features, and interactive mechanics while optimizing performance across PC, mobile, and console. Collaborate with creative, product, engineering, QA, clients, and stakeholders from concept through delivery. Use GitHub and Rojo in team workflows, troubleshoot technical issues, and apply scalable data-handling and platform-innovation techniques.

Full Stack Engineer responsible for building responsive frontends (JS/TS, React preferred) and backend services (Python, Go, or Node.js/TypeScript), designing RESTful APIs, managing databases (Postgres/MongoDB), and deploying on cloud (AWS). Collaborate with teams, optimize performance, and apply DevOps practices (Docker, Kubernetes, CI/CD). Requires strong problem-solving, communication, and 3+ years of experience.

Create graphics, videos, data visualizations, social content, email assets, merchandise, and event branding. Translate complex data and long-form content into accessible visual stories, develop brand identity, maintain a marketing asset library, and rapidly test and refine creative variants based on engagement and conversion results. Collaborate closely with marketing and engineering while managing a fast-paced, campaign-driven workflow.

Own the full sales cycle across agency accounts, from prospecting through close. Build executive relationships within creative, advertising, media, production, and technology organizations; develop account strategies; expand adoption; manage pipeline and forecasting; and help shape the agency sales strategy. Partner with Product and Marketing to translate customer feedback into product and go-to-market opportunities. The role requires strong agency ecosystem knowledge, complex B2B sales experience, commercial judgment, and enthusiasm for generative AI.

Develop, train, evaluate, and deploy machine learning models and AI-powered applications. Responsibilities include data preprocessing, feature engineering, deep learning development, cloud-based model deployment, and collaboration with data engineers, MLOps teams, and business stakeholders. The role also requires applying strong analytical and research skills while staying current with advances in artificial intelligence.