Top Entry Level Artificial Intelligence Jobs

Lead hands-on verification for complex networking ASICs from strategy and test planning through coverage closure and tape-out. Develop SystemVerilog/UVM environments, testbenches, sequences, checkers, scoreboards, and constrained-random tests. Debug RTL and simulation failures, drive functional/code/assertion coverage, and collaborate with architecture, RTL, physical design, firmware, emulation, and silicon teams. Establish quality gates, manage verification risks, support full-chip validation, and ensure tape-out and post-silicon readiness.

Build and maintain mission-critical wealth management systems for SMB clients. Design data pipelines, ETL/ELT processes, data models, warehouses, analytics, and reporting solutions using AWS, Snowflake, Mage AI, and other big data tools. Collaborate with data scientists and analysts on predictive models, statistical analyses, and machine learning algorithms. Develop software with Next.js and Python while working closely with the team and clients on financial-domain challenges.

Own the research-engineering loop for turning base models into capable, reliable agents. Design RL environments, training and evaluation data, post-training experiments, reward systems, and regression suites. Analyze model behavior, diagnose reward hacking and other failures, improve distributed training and rollout infrastructure, and translate successful research into reproducible production pipelines. The role requires strong Python and software-engineering skills, modern language-model experience, deep-learning knowledge, and reinforcement-learning intuition.

Own full-cycle recruiting for contract and consulting roles focused on SAP and Oracle consultants across the U.S., Canada, and Mexico. Build specialized talent pipelines, develop sourcing strategies for hard-to-find enterprise technology skills, and manage multiple contractor searches supporting customer projects. The role requires strong knowledge of contingent workforce recruiting and systems integrator ecosystems.

Coordinates ON.energy’s branding operations, including merchandise, printed materials, signage, vehicle branding, events, conferences, inventory, schedules, documentation, and vendor relationships. Reviews proofs and samples for brand compliance, tracks deliverables, manages logistics across offices and operating sites, supports award submissions, and assists with event setup and teardown. The role is based onsite in Miami and requires periodic travel.

Lead research and evaluation of an AI-powered, physics-informed climate model designed for accurate multidecadal forecasts. Develop training and testing cases, implement model improvements for generalization to unseen climates, couple atmospheric, oceanic, land, and sea-ice systems, publish findings, contribute open-source code, collaborate with researchers, and mentor interns.

Build and maintain a large case law dataset through document metadata pipelines, web scraper reliability systems, citation-resolution utilities, APIs, and evaluation benchmarks. The role requires backend technical generalism, data pipeline expertise, and basic-to-intermediate infrastructure and DevOps skills. Python and SQL are core, while ML and AI experience is beneficial. This is an in-person position in SoHo, New York City.

Own the workflow engine powering customer runs, including scheduling, queues, retries, batching, idempotency, provider integrations, observability, and cost controls. Scale Postgres and Redis while improving reliability across high-volume data workflows. Work autonomously, use coding agents extensively, and make technical decisions for an early-stage platform.

Own end-to-end recruitment for go-to-market roles across the US, including sourcing passive candidates, partnering with hiring managers, managing interview processes, and guiding candidates through offers. The role requires representing Unframe’s mission, improving hiring structure and pace, and supporting rapid growth in an AI startup environment.

Advance AI data and agentic environment creation by designing scalable pipelines combining automated generation, real-world data, and expert judgment. Run experiments, evaluate data and model performance, collaborate with engineering, product, customers, and domain experts, and translate research prototypes into production workflows. The role also involves developing expert-authoring workflows, monitoring frontier research, and representing findings through publications, talks, blogs, and customer engagements.