Top Artificial Intelligence Jobs

Own the full lifecycle of production classification and detection models, including transformer fine-tuning, entity detection, behavioral risk scoring, training, serving, versioning, evaluation, drift detection, and retraining. Build SageMaker-based ML systems and define output contracts supporting audit and policy enforcement. Lead the evaluation harness and mentor a co-op while operating as the company’s sole ML engineer.

Work directly with the CEO as a Chief of Staff MBA intern: build operations and meeting cadences, manage projects and dashboards, plan events, conduct market and competitive research, drive cross-functional strategic initiatives, and influence product design and roadmap decisions. In-office five days a week with long hours; hands-on startup experience expected.

Build and own large-scale backend and full-stack systems supporting AI agents, data integrations, sync engines, and construction financial products. Design major subsystems, make architecture and build-versus-buy decisions, debug complex production issues, improve scalability and performance, and mentor engineers. Work across cloud infrastructure, distributed systems, legacy on-premise integrations, caching, data consistency, and AI-powered workflows while collaborating directly with founders and customers.

Perform outbound prospecting (email, calls, social) to generate qualified healthcare leads, research targets, craft personalized messaging, qualify prospects, maintain CRM records, book meetings, and collaborate with the founder to optimize outreach and meet weekly/monthly performance goals.

Build Kastle’s growth engine by mapping target accounts, developing outbound campaigns, creating automated growth tools, owning product messaging, managing events, and testing creative ways to reach senior buyers. The role combines writing, campaign execution, data analysis, AI-enabled automation, lead tracking, sales enablement, and continuous experimentation to generate qualified sales opportunities across financial-services markets.

Own Synthetic’s visual identity across brand, marketing, and product. Define and maintain the brand, design and build websites and launch materials, and implement product features in TypeScript and SvelteKit alongside engineers. The role requires shipping designs directly, working across multiple design disciplines, and moving quickly in an early-stage, in-person startup environment.

Manage office operations, supplies, vendors, facilities, events, travel, and budgets. Coordinate interviews, offer letters, new-hire paperwork, onboarding logistics, equipment, system access, and schedules. Provide administrative support to leadership, assist with meetings and follow-ups, and improve workflows as the startup scales. This is an onsite role five days per week in San Francisco.

Leads Dust’s global Solutions Engineering organization across pre-sales and post-sales. Builds the team, operating model, hiring strategy, career paths, and technical standards while personally supporting strategic enterprise evaluations. Owns technical wins, deployment handoffs, advanced customer adoption, expansion, reusable playbooks, and cross-functional alignment with Sales, Customer Success, AI Deployment, Product, and Engineering. Requires strong expertise in enterprise architecture, integrations, security, governance, AI systems, and customer-facing technical leadership.

Own the full sales cycle for mid-market and enterprise accounts, including prospecting, pipeline generation, discovery, tailored demos, negotiation, and closing. Sell complex SaaS solutions to CFO and finance stakeholders, manage multiple opportunities, maintain accurate forecasts and pipeline hygiene, and provide market and customer insights to internal teams. This is an in-person role based in San Francisco or New York.

Own and execute supply chain strategy for electromechanical robotic products, managing sourcing, procurement, inventory, logistics, supplier performance, and NPI-to-production transitions. Partner with engineering, manufacturing, quality, finance, and operations to mitigate risks, drive cost-down/value-engineering, establish material planning and inventory strategies, track KPIs, and improve ERP/MRP systems to scale reliable production.