Paper-posted 13 days ago
$160,000 - $190,000/Yr
Full-time • Mid Level
Remote
1,001-5,000 employees

We are seeking a Senior AI Engineer to design, develop, and operationalize the first B2B In-Classroom Tutor AI. Using cutting-edge AI solutions that power critical product features across our platform. You’ll work hands-on across the full machine learning lifecycle. From experimentation to deployment, you will be helping to shape the future of AI at scale for millions of learners and educators. In this role, you’ll collaborate closely with Product, Data, and Engineering teams to build both trained (supervised and unsupervised) and prompt-based AI systems . You’ll balance technical depth with creativity, ensuring that our AI implementations are effective, scalable, and responsible. Paper is reimagining how schools support students so that every learner can reach their full potential. Our vision is a world where every student receives timely, personalized, and relevant academic support. We offer a suite of scalable solutions including 24/7 tutoring, writing feedback, math practice, college and career support, and AI-powered instructional tools that provide personalized support to all students, including multilingual learners. Our GROW high-impact tutoring program accelerates learning through targeted small-group instruction, delivers measurable gains in student achievement, and eases teacher workloads. Trusted by 500+ school districts across 40+ states and backed by leading investors including IVP, Sapphire Ventures, Framework Capital, and Reach Capital, we’re pursuing a bold goal: to drive the best academic outcomes for as many students as possible. Recent articles: GROW by Paper Drives 201% Increase in Grade-Level Proficiency in Just 12 Weeks GROW by Paper Earns Stanford’s NSSA Tutoring Program Design Badge, Signaling Excellence in Research-Aligned Design Paper Appoints Marisa Burkhart as CRO

  • AI Solution Development: Design, implement, and deploy AI-powered features, including model training, fine-tuning, and prompt engineering workflows (e.g., leveraging LLMs and multi-modal architectures).
  • Collaboration & Delivery: Work cross-functionally with Product Managers, Software Engineers, and Data Scientists to translate product requirements into robust, production-ready AI solutions.
  • Technical Execution: Own the end-to-end lifecycle of AI initiatives—from data manipulation and model experimentation to deployment, monitoring, and continuous improvement.
  • Performance & Reliability: Optimize models and infrastructure for scalability, latency, and cost efficiency. Partner with DevOps and MLOps to ensure reliable and maintainable AI pipelines.
  • Innovation & Research: Stay current with the latest AI advancements (e.g., LLMs, RAG, multi-modal models) and drive rapid experimentation to identify opportunities for impactful innovation.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or related field.
  • 5+ years of experience developing production-grade AI/ML systems.
  • Proven success delivering both trained (supervised, unsupervised, etc.) and prompt-based (LLM-powered, few-shot, etc.) solutions.
  • Experience evaluating and monitoring model performance with robust testing and validation protocols.
  • Strong programming skills in Python and experience with frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, or OpenAI APIs.
  • Deep understanding of the full ML lifecycle—data pipelines, model training, inference, and monitoring.
  • Experience operationalizing LLMs and prompt-engineering workflows.
  • Familiarity with distributed systems and cloud infrastructure for AI workloads (e.g., AWS, GCP, Azure).
  • Excellent communication and collaboration skills; able to work effectively in cross-functional environments.
  • Strong problem-solving abilities with a focus on translating complex AI concepts into real-world product value.
  • Proactive, detail-oriented, and driven by continuous learning and experimentation.
  • Experience with multi-modal or retrieval-augmented generation (RAG) systems is a plus.
  • Experience in EdTech or education-related products.
  • Familiarity with regulatory or ethical considerations in ML model development and evaluation.
  • Comprehensive & competitive compensation, health benefits, retirement plan, stock options, and more.
  • In addition to vacation days, we provide Paperites with sick days and 4 extra weeks off - including statutory holidays, Paper Days throughout the year, and a full Paper Week from Dec 25 to Jan 1.
  • A $500 stipend to set-up your workspace and $100 monthly stipends to support with on-going workspace needs.
  • We support growing families with generous paid parental leave.
  • Unlimited access to tutoring and educational support for children of Paper employees.
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