Top Artificial Intelligence Jobs

Own the company’s full-cycle talent strategy, from defining roles and mapping markets to sourcing, closing, and candidate care. Personally lead senior technical searches while partnering with founders and hiring managers. Build, operate, and debug recruiting agents; establish evidence-based assessments, work trials, reporting, and sourcing systems. The role requires strong technical fluency, executive search ability, offer negotiation skills, and networks in San Francisco or Shanghai.

Own the SentinelAgent clinical trial AI platform from early pilots through validated, multi-sponsor deployment. Responsibilities include product requirements, backlog and roadmap management, engineering coordination, regulated integrations, GxP validation, AI governance, privacy and security controls, release gates, auditability, and performance instrumentation. The role requires extensive eClinical product management experience, clinical systems integration literacy, knowledge of global regulations, and experience shipping locked-model AI products in validated environments.

Own brand accounts and lead end-to-end influencer marketing campaigns for U.S. clients. Manage creator strategy, budgets, negotiations, approvals, launches, reporting, and performance reviews while translating campaign data into recommendations. Build long-term relationships, identify upsell opportunities, manage escalations, coordinate internal teams, contribute to forecasting, and mentor teammates.

Own the B2B product experience from enterprise enrollment through renewal and expansion. Lead customer discovery, intake, roadmap prioritization, enterprise integrations, onboarding, engagement, analytics, and AI-powered learning insights. Partner closely with sales, customer success, engineering, legal, and enterprise customers to deliver admin tools, reporting, LMS and SSO integrations, measurable learning outcomes, and improved activation, retention, and expansion.

Own ML engineering infrastructure from experimentation and labeling through data tooling, model deployment, orchestration, inference, and production reporting. Build systems for live A/B testing, scalable training data, nightly pipelines, quality monitoring, and jobsite onboarding. Lead hands-on development while growing the engineering team, managing GPU and cloud costs, and debugging issues across models, data, and pipelines.

Leads external robotics and AI engagements from planning through execution. Responsibilities include defining scope, resources, milestones, staffing, logistics, and operational playbooks; coordinating partners, researchers, hardware, and infrastructure teams; resolving tradeoffs; overseeing on-site deployments; and building scalable engagement operations.

Own retention, renewals, churn prevention, and expansion for a high-volume, low-touch B2B SaaS customer segment. Handle cancellation and commercial requests, respond to automated outreach, identify expansion opportunities, maintain Salesforce records and forecasts, and monitor performance metrics. Partner with CX, Billing, and RevOps while improving automation, messaging, and customer engagement processes.

Own platform positioning, messaging, competitive strategy, and go-to-market execution for MISUMI Americas’ digital manufacturing platform. Partner with Product, Engineering, Sales, and Marketing to translate AI, sourcing, and manufacturing capabilities into compelling value propositions. Develop persona-specific content, launch campaigns, sales enablement, product training, case studies, and customer insights. The role requires manufacturing or supply chain technology expertise, SaaS marketing experience, strong technical writing, and travel up to 25% annually.

Build and grow the insurance business by creating demand, sourcing and qualifying enterprise opportunities, developing quantified value cases, and leading complex multimillion-dollar technology sales through close. The role coordinates product, engineering, deployment, legal, security, and procurement stakeholders; informs product strategy through customer insights; and develops repeatable sales processes. Candidates need deep insurance domain expertise, enterprise sales experience, technical AI fluency, and a record of independently closing complex engagements.

Conduct research on AI tokenomics by evaluating model architecture trends, building simulation models for training and inference efficiency across hardware and workloads, diligencing companies using model tokens, and forecasting economic impacts for investors, corporates, and policymakers.