Top Entry Level Artificial Intelligence Jobs

Conduct cold outreach to tax and accounting firms, book qualified meetings, manage follow-ups and pipeline hygiene, research prospects, learn and communicate a complex AI product, refine messaging, and share market feedback. The role supports Nylon’s US market launch from its Brighton office and requires motivation, resilience, coachability, strong verbal communication, pace, and high agency.

Build agentic workflows for clinical trial automation and reliable systems for document ingestion, data transformation, validation, and auditability. Own frontend, backend, data infrastructure, and AI orchestration across the product. Collaborate with clinical teams to convert complex workflows into production software while meeting regulated healthcare standards. Work directly with founders, move quickly through ambiguous technical problems, and help establish engineering culture at an early-stage company.

Lead public marketing for an early-stage startup transforming mathematical research through management and AI assistance. Responsibilities include increasing awareness among mathematicians and broader society, representing the company publicly at research, media, and government events, and developing campaigns to make Talmenta well known. The role offers substantial autonomy, mentorship, equity, and either full-time employment or an initial part-time freelance arrangement.

Develop and launch Matterstack’s laboratory operations from the ground up. Responsibilities include defining lab requirements, securing external lab access, selecting and outfitting a facility, hiring and leading staff, purchasing equipment, building supplier networks, integrating laboratory IT, managing budgets, and planning future expansion and automation. The role requires close collaboration with scientists, engineers, executives, vendors, investors, lawyers, and government stakeholders, with co-location at the eventual facility and occasional travel.

Build and scale Tamarind Bio’s computational biology platform, including infrastructure, APIs, web interfaces, ML services, and deployment systems. Partner with founders and customers to define products, ship features, operate reliable services, and support AI-powered drug discovery workflows. Responsibilities span AWS DevOps, MLOps, frontend development, HPC scaling, model deployment, architecture, coding, design reviews, and practical production operations.

Build Mesh’s financial governance platform from the ground up, partnering with founders and customers to architect and ship backend infrastructure, AI agentic workflows, enterprise integrations, data pipelines, spreadsheet interpretation, evaluation systems, and auditability tooling. The role owns problems end-to-end, from customer discovery and product design through production deployment and iteration, while operating across AI systems, developer tooling, and enterprise software.

Summer Robotics develops microsecond-precise, continuous-streaming 3D perception hardware and software for robotic assembly and inspection. The company serves automotive and semiconductor manufacturing customers and is scaling its industrial automation platform from a Campbell, California startup.

Lead video editor responsible for producing long- and short-form content, motion graphics, promotional assets, and select design projects. The role involves hands-on editing, visual storytelling, AI-assisted content creation, developing templates and visual standards, and managing freelance creative contractors. The editor will collaborate with founders and internal teams to shape the company’s visual identity across video, social, web, and promotional channels.

Enterprise Account Executive responsible for managing enterprise customer accounts and driving sales growth. The demo posting provides no further details about duties, qualifications, compensation, travel, or work authorization.

Own the end-to-end ML lifecycle platform, including training-as-a-service, experiment tracking, model CI/CD, data versioning, monitoring, and cost governance. Build infrastructure for multi-GPU training, automated evaluation gates, canary releases, A/B testing, and checkpoint management. Partner with ML Scientists to improve reproducibility and workflow efficiency, integrate external model providers, and help guide platform direction while mentoring engineers.