Top Entry Level Artificial Intelligence Jobs

Supports marketing projects, events, social media, brand initiatives, content creation, and product marketing. Responsibilities include coordinating timelines and deliverables, writing website and campaign copy, producing case studies and social content, managing event logistics, proofreading materials, and assisting with product launches and sales enablement. The role suits an organized, curious early-career marketer who can write clearly, work independently in ambiguity, and collaborate across teams.

Maintain and improve the GutLab hardware fleet through inspection, repair, firmware updates, deployment preparation, and redeployment. Partner with laboratory and operations teams to troubleshoot electro-mechanical issues, document failures, investigate root causes, and implement fixes. Support next-generation hardware development from design through assembly, including mechanical design and performance iteration. This hands-on entry-level role requires adaptability, organization, strong communication, and enthusiasm for life sciences technology in a startup environment.

Lead finance strategy and operations for a rapidly growing healthcare company. Own forecasting, financial modeling, budgeting, cash flow, KPI and investor reporting, accounting oversight, tax compliance, and financial infrastructure for the MSO and affiliated professional corporations. Partner with senior leaders to monitor performance, address risks, and guide corrective actions. The role reports to the CEO and offers a pathway to Chief Financial Officer.

Lead and scale Doji’s user-generated content program as a user acquisition channel. Responsibilities include recruiting, onboarding, managing, and retaining creators; streamlining briefs, production, feedback, posting, tracking, and payments; setting creative standards; running weekly content tests; measuring installs and activated users; and building systems and automation to scale quality UGC operations.

Own full-cycle mid-market B2B SaaS sales, including prospecting, lead generation, relationship building, deal execution, and quota attainment. The role involves autonomously pursuing opportunities ranging from $50,000 to seven-figure annual contracts, managing complex 6–9 month sales cycles, developing sales processes and materials, and working closely with a fast-growing startup team.

Own product prioritization and execution across product, engineering, go-to-market, and partners. Translate roadmap priorities into plans, coordinate testing and releases, manage dependencies and risks, convert customer feedback into product inputs, support partner onboarding, and lead cross-functional initiatives such as feature launches and integrations. The role also establishes repeatable processes for planning, delivery, and continuous improvement in an early-stage company.

Troubleshoot complex Linux, NVIDIA GPU, CUDA, Docker, virtualization, networking, hardware, and AI workload issues. Own escalated support tickets, assist clients and infrastructure suppliers, identify root causes, and collaborate with engineering teams. Build Python and Bash diagnostic tooling, create runbooks, improve monitoring and troubleshooting processes, and support supplier onboarding and machine management. The role is fully or mostly on-site in Los Angeles, with schedules covering Monday-Friday or Sunday-Thursday.

Open application opportunity at Intelligence, an AI product lab developing platforms to evaluate frontier multimodal models and operating products including Design Arena. The company is based in San Francisco, sponsors visas, supports relocation, offers competitive salary and meaningful equity, and follows a Sunday–Friday schedule.

Design and deploy AI-enabled decision workflows for Department of Defense and federal customers. Translate operational challenges into data models, dashboards, AI agents, automated workflows, and predictive or prescriptive solutions. Engage stakeholders, analyze and troubleshoot data, advise end users, support adoption, and collaborate with developers to improve the platform. The role combines solution engineering, analytics, customer advisory, data integration, and AI workflow design.

Lead and scale a research team from 5 to 20 researchers developing frontier machine learning systems for forecasting, optimization, and control. The role requires strong ML foundations, hands-on experience training and deploying production models, and first- or second-line management experience. Preferred qualifications include LLM infrastructure expertise, quantitative modeling experience, and startup experience. This is an in-person role in San Francisco, five days per week.