Top Remote Entry Level Artificial Intelligence Jobs

Create character reference sheets, props, environments, and visual assets for animated series. Establish cohesive visual languages, design rules, and visual storytelling systems across varied styles. Collaborate with showrunners, writers, animators, AI filmmakers, and creative leads; translate scripts and creative direction into clear references; iterate quickly; and optimize assets for AI image- and video-generation workflows.

Own and scale high-volume outbound email infrastructure supporting 500K+ monthly emails across client accounts. Responsibilities include optimizing deliverability, designing domain and inbox architecture, building campaign experimentation systems, refining LLM-powered personalization workflows, monitoring performance metrics, creating operational playbooks, and partnering with product and engineering teams to automate the outbound platform.

Own FAR.AI’s internal IT and security function, including accounts, devices, identity and access management, onboarding, offboarding, office networking, support, endpoint hardening, data protection, governance, and vendor risk. The role will remediate security gaps using threat modeling, automate self-service infrastructure, partner across teams, communicate and manage change, and hire and lead an IT Coordinator.

Designs and maintains automated end-to-end and API tests using Cypress, WebDriverIO, and Karate. Develops test scripts with JavaScript or TypeScript in Node.js environments, executes test suites, analyzes results, identifies defects, and collaborates with engineering teams on resolution. The role contributes to test strategy, regression and performance testing, code reviews, test coverage, and continuous quality improvements.

Build code, integrations, documentation, benchmarks, and reference implementations for a macOS and Apple Silicon compute platform. Operate workloads, debug issues across application and infrastructure layers, support developers, improve tooling and products, and represent developer needs internally. The role also involves technical writing, workshops, open-source engagement, performance analysis, and collaboration across platform, networking, fleet, product, and engineering teams.

Administer and extend CRM, contact center, and AI-agent platforms supporting Customer Operations. Configure workflows, routing, permissions, prompts, knowledge sources, integrations, and automations. Troubleshoot data-flow issues, monitor AI performance, document system configurations, maintain runbooks, train users, evaluate tools, and translate business requirements into reliable system configurations.

Build and operate CrewAI’s cloud and enterprise infrastructure across AWS, Azure, and GCP. Develop CI/CD pipelines, deployment automation, observability, security controls, self-hosted installation tooling, and reliability processes. Support containers, Kubernetes, databases, queues, networking, secrets, and production workloads. Participate in incident response and on-call operations while partnering with runtime and product engineering teams to improve deployment safety, scalability, and customer production environments.

Periodic Labs invites exceptional candidates to submit a general application for future opportunities at its AI and physical sciences laboratory. The team develops advanced models aimed at enabling novel scientific discoveries and values ownership, independent problem-solving, continuous learning, and interdisciplinary exploration.

Own presales discovery, solution architecture, technical demos, prototypes, proof-of-concept definition, technical evaluations, RFP responses, and security questionnaires for enterprise AI customers. Translate customer workflows and technical requirements into validated architectures and measurable business value, manage implementation risks, and provide accurate delivery handoffs. Convert field insights into reusable reference architectures, demos, and product improvements.

Design, develop, test, and optimize safe, scalable real-time software for production autonomous vehicle systems. Architect continuous learning infrastructure for ML model deployment and monitoring, analyze algorithms, and collaborate with embedded, platform, AI, sensor, and compute teams. Support perception, prediction, and planning integration while contributing to highway and urban autonomous driving capabilities.