AI/ML Engineer - Higher Ed

We believe in the power and joy of learning At Cengage, our employees have a direct impact in helping students around the world discover the power and joy of learning. We are bonded by our shared purpose – driving innovation that helps millions of learners improve their lives and achieve their dreams through education. Cengage's portfolio of businesses supports student choice by providing a range of pathways that help learners achieve their goals and lead a choice-filled life. Our culture values inclusion, engagement, and discovery Our business is driven by our strong culture, and we know that creating an inclusive workplace is absolutely essential to the success of our company and our learners, as well as our individual well-being. We recognize the value of diverse perspectives in everything we do, and strive to ensure employees of all levels and backgrounds feel empowered to voice their ideas and bring their authentic selves to work. We achieve these priorities through programs, benefits, and initiatives that are integrated into the fabric of how we work every day. To learn more, please see https://www.cengagegroup.com/about/inclusion-and-belonging/ . The AI/ML Engineer – Higher Education builds AI capabilities for Cengage's higher education products to improve student engagement, learning outcomes, and instructor productivity. You will design, build, and ship production AI features integrated directly into platforms used by millions of students and faculty. This role requires a builder who ships weekly, cares about learning science, and can design AI experiences that genuinely improve educational outcomes. The ideal candidate has experience shipping production ML or LLM features, understands the nuances of higher education workflows, and balances research-driven thinking with shipping discipline. Key Responsibilities HED AI Feature Development Ship and improve AI features weekly across Cengage HED platforms Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback Develop Instructor Insight Assistant features for course analytics and at-risk student identification Create Content Studio capabilities for AI-assisted content authoring and adaptation Integrate LLMs, RAG systems, and agentic workflows into HED platform architectures Platform Integration & Engineering Integrate AI features into existing HED platform architectures and data systems Partner with platform engineering on API design, scaling, and production deployment Build retrieval systems against Cengage's proprietary content library (books, assessments, media) Ensure AI features meet FERPA compliance and accessibility standards (WCAG, DOJ) Resolve technical blockers and production issues with urgency Measurement & Optimization Monitor feature usage, engagement, and learning outcome impact Track and improve model performance on quality, cost, and latency dimensions Partner with learning scientists and researchers on efficacy measurement Iterate rapidly based on student feedback, instructor feedback, and usage telemetry Maintain documentation and engineering runbooks for deployed AI features Required Qualifications Bachelor's degree in Computer Science, Engineering, or related field 4+ years of experience in software engineering, with at least 2 years focused on AI/ML Strong proficiency in Python with experience building production ML or LLM systems Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock) Experience with RAG architectures, vector databases, and embedding models Solid software engineering fundamentals including testing, CI/CD, and system design Experience shipping production features at scale (thousands or millions of users) Strong communication skills to work with product, design, and research partners Preferred Qualifications Experience in EdTech or adjacent domains with production education AI features Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI) Background in learning science, educational psychology, or instructional design Experience with FERPA compliance and education-industry data handling Familiarity with accessibility standards (WCAG, Section 508, DOJ accessibility) Experience with fine-tuning, LoRA, or custom model training Tools & Technologies You should be comfortable with many of the following: Languages: Python, JavaScript/TypeScript, SQL AI/ML: OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face Vector DBs: Pinecone, Weaviate, pgvector, Chroma Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI Data: Snowflake, Databricks, Postgres, Redis DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines Key Competencies Shipping Mindset — delivers features weekly, not quarterly Technical Craft — writes clean, tested, production-grade code Learning Orientation — cares about whether AI actually improves learning outcomes Systems Thinking — sees the full platform and integrates AI cleanly Collaboration — partners effecti