Top Entry Level Artificial Intelligence Jobs

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.

Build and launch customer-facing AI applications by developing frontend and backend features, integrating APIs, AI services, databases, and business tools, and improving reliability and usability. Independently manage features from requirements through deployment, troubleshoot AI-generated code, and collaborate with developers. Applicants may be self-taught or early-career and should demonstrate completed applications through employment, freelance work, or personal projects.

Own the architecture, reliability, scalability, and developer experience of a Kubernetes-based platform supporting secure enterprise workloads. Design resilient infrastructure, define SLOs, improve observability and operational workflows, and build self-service deployment and developer tooling. Partner with product engineering and leadership to establish technical standards, resolve architectural risks, and scale infrastructure for significant customer growth.

Build internal software for field collection operations, including tasking, site setup, device inventory, shift tracking, local tools, and site-health monitoring. Improve operational efficiency by observing field workflows, removing bottlenecks, and making site expansion repeatable. Integrate field tools with data infrastructure and marketplace incentives, while collaborating closely with on-the-ground teams and occasionally traveling to field sites.

Acts as the founder’s right hand across sales and go-to-market execution, operations, hiring, special projects, and automation. Owns high-priority outcomes, creates structure in ambiguous situations, drives pipeline and deals, recruits talent, researches and ships projects, and builds AI agents to automate repetitive work. The role requires exceptional agency, judgment, resilience, ownership, and comfort operating across multiple functions in a fast-growing startup.

Adapt English literary prose into Tibetan while preserving the source author’s idealistic, visionary, and reflective voice, tone, intent, and structure. The contractor will complete a paid sample, translate content across technical and humanities subjects, and deliver high-quality literary transcreation. Native-level Tibetan fluency, strong writing ability, and demonstrable literary translation or transcreation experience are required. Work is flexible and project-based, with fluctuating availability and a typical minimum commitment of 2 hours daily or 10 hours weekly.

Owns US B2B partner acquisition for a homeowner seller-referral marketplace. Responsibilities include prospecting, negotiating referral terms, launching partner workflows, measuring channel performance, improving partner economics, documenting acquisition playbooks, and coaching a small partnerships team.

Designs and documents ASIC modules, supports pre-silicon simulation and verification, develops hardware and software test systems, and validates and characterizes chips. The engineer will document test plans, debug root causes, and work across analog, digital, and post-silicon validation activities in an on-site startup environment.

Serve as a resident technical advisor embedded with strategic client accounts. Lead architecture, implementation, and adoption of the Databricks Platform, translating business requirements into technical solutions and helping clients maximize data, analytics, and AI investments on their selected cloud platform.

Conduct industry-focused AI research on autonomous agents and world models. Develop models involving large language models, active inference, and optimal policies, including architecture experimentation, fine-tuning, deep-learning agent development, and action optimization. Candidates will work on real-world enterprise problems while pursuing cutting-edge research during a fixed-term three- or six-month fellowship.