nativeads.ai
AI Engineer (New Grad)
Palo Alto, California • in-person • full-time
paid
Job description
About Nativeads.ai Nativeads.ai is building the Cursor for Advertising — an AI-native creative platform that enables brands and retailers to generate, personalize, and optimize on-brand advertising content at scale. Named a top-6 AI startup to watch by AdExchanger (Dec '25), we sit at the intersection of Large Language Models, creative generation, retail media, and performance optimization. We partner with leading retailers including Walmart Connect and are backed by early-stage investors. 2026 is a breakout year. This is your chance to join at the very beginning. The Opportunity - We are not looking for someone who has done it before. We are looking for someone who cannot wait to figure it out. - This role is for a new grad or intern-experienced engineer who has shown — through coursework, side projects, open-source contributions, or internship work — that they move fast, learn obsessively, and ship things. You will work directly with our CTO, embedded in the core AI team, building and iterating on the systems that power creative generation for global brands. - You will be given real responsibility from day one. That is not spin — it is the nature of a 0→1 startup. If that excites you more than it scares you, read on. What You Will Work On - Contribute to the AI pipeline that generates and personalizes advertising content using multimodal models (text, image, video) - Build and run evaluations that measure output quality — no vibes, just rigorous benchmarks - Assist in fine-tuning and adapting LLMs and image generation models for brand-specific use cases - Help design and implement agentic workflows that automate complex creative tasks end-to-end - Monitor model performance in production and iterate quickly when things break or drift Research emerging models and techniques and bring concrete proposals back to the team What We Are Looking For Required - A CS, ML, or related degree (or equivalent demonstrated skill — we care about what you built, not where you went) - Solid Python fundamentals and comfort reading and writing production-quality code - Foundational understanding of machine learning: model architectures, training, inference, and evaluation - At least one shipped project involving LLMs, image generation, or ML systems — coursework, personal project, or internship all count - A documented habit of going deep: blog posts, GitHub activity, competition results, or research that shows you do not stop at surface understanding - Hunger. The ability to sit with ambiguity, figure things out, and ship something before asking for permission Strongly Preferred - Hands-on experience with PyTorch or a major ML framework beyond homework assignments - Familiarity with image generation models (Stable Diffusion, Flux, DALL-E) or video foundation models - Exposure to fine-tuning techniques (LoRA, adapters, instruction tuning) — even if just experimental - Experience building or experimenting with agentic or multi-step LLM workflows - Any internship or co-op experience where you shipped something real to production The Mindset We Hire For - You learn by building, not reading. You have broken things, fixed them, and broken them again. - You are rigorous about quality. You run evals, not vibe checks. - You own your work. You do not wait to be told what to do next - You want to understand things at a level most people do not bother with.You are more energized by a hard problem than a comfortable one. Compensation - Competitive Bay Area–aligned new grad salary - Meaningful early equity - Direct mentorship from experienced AI engineers - Flexible work environment - The rarest thing: a seat at the table when it actually matters
About the company
Nativeads.ai is building the Cursor for Advertising — an AI-native creative platform that enables brands and retailers to generate, personalize, and optimize on-brand advertising content at scale. Named a top-6 AI startup to watch by AdExchanger (Dec '25), we sit at the intersection of Large Language Models, creative generation, retail media, and performance optimization.