AI \ ML Engineer R&D

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/ 

Position Overview

The AI/ML Engineer for R&D is a high-output, full-stack engineering role aimed at quickly producing fully functional AI-powered application prototypes. This is a hands-on position for a versatile engineer who acts swiftly, codes in multiple languages, and uses AI-assisted development tools to considerably accelerate delivery.  

Your role involves turning concepts into functional applications, not simply mock-ups or wireframes. You will build prototypes that prove business value and technical feasibility. The ideal applicant is proficient in modern programming languages and has strong experience working with AWS and Azure clouds. You adopt AI-forward development techniques using tools like GitHub Copilot, Claude, and other AI coding assistants. You have engineering-level knowledge of LLMs and core AI/ML concepts and can integrate these technologies into production-ready software.  

Key Responsibilities

Rapid Prototype Development

• Produce fully working AI-enhanced application prototypes swiftly—from initial concept to working demonstration in just days

• Develop end-to-end solutions including backend services, APIs, data pipelines, and frontend interfaces

• Transform business requirements and technical concepts into tangible, demonstrable applications

• Iterate rapidly based on feedback, adjusting quickly to refine or redirect prototypes

• Create reusable code libraries, templates, and scaffolding to accelerate future development

• Ensure prototypes are sufficiently robust to support collaborator demos and user testing  

AI-Assisted & AI-Forward Development

• Leverage AI coding assistants (GitHub Copilot, Claude, Cursor, Codex) to improve development speed and quality

• Keep up to date with new AI development tools and incorporate them into everyday workflows

• Use LLMs for code generation, debugging, refactoring, documentation, and test creation

• Develop prompt engineering techniques to optimize AI-assisted coding output

• Contribute to team guidelines for AI-augmented software development

• Assess and suggest new AI development tools and methodologies  

Cloud Engineering & Infrastructure

• Develop and launch applications on AWS and Azure cloud platforms with deep fluency in both

• Leverage managed AI/ML services including AWS Bedrock, SageMaker, Azure OpenAI, and Azure ML

• Implement serverless architectures (Lambda, Azure Functions) for rapid, scalable deployments

• Design and build containerized applications using Docker and Kubernetes

• Configure cloud infrastructure using IaC tools (Terraform, CloudFormation, Bicep)

• Optimize for cost, performance, and security in cloud environments  

AI/ML Integration & Engineering

• Integrate LLMs and foundation models into applications with deep understanding of their capabilities and limitations

• Implement RAG (Retrieval-Augmented Generation) architectures, vector databases, and embedding pipelines

• Build prompt engineering solutions, fine-tuning workflows, and model orchestration patterns

• Build agentic AI systems and multi-step reasoning workflows

• Apply core ML principles including model evaluation, inference optimization, and responsible AI practices

• Connect AI capabilities to enterprise data sources, APIs, and existing systems  

Technical Skills

Languages & Frameworks

• Primary: Python (FastAPI, Flask, Django), JavaScript/TypeScript (Node.js, React, Next.js)

• Secondary: Go, Rust, Java, or C# – ability to pick up new languages quickly

• AI/ML: PyTorch, TensorFlow, LangChain, LlamaIndex, Hugging Face Transformers

• Data: SQL, pandas, Apache Spark; experience with vector databases (Pinecone, Weaviate, pgvector)   

Cloud Platforms

• AWS: Lambda, Step Functions, Bedrock, SageMaker, S3, DynamoDB, API Gateway, ECS/EKS, EventBridge

• Azure: Functions, OpenAI Service, ML Studio, Cosmos DB, Container Apps, API Management

• Infrastructure: Terraform, CloudFormation, Docker, Kubernetes, CI/CD pipelines (GitHub Actions, GitLab CI)  

AI Creation Tools

• AI Programming Helpers: GitHub Copilot, Claude, Cursor, Amazon CodeWhisperer, Codeium

• LLM APIs: OpenAI, Anthropic Claude, AWS Bedrock, Azure OpenAI, Google Vertex AI

• Development: VS Code, JetBrains IDEs, Jupyter notebooks, Git version control  

Required Qualifications

• Bachelor's degree in computer science, Software Engineering, or related field; or equivalent experience

• 5+ years of professional software engineering experience building production applications

• Solid experience in Python and JavaScript/TypeScript; familiarity with at least one other programming language

• Extensive practical experience working with both AWS and Azure cloud platforms

• Demonstrated experience building AI/ML-powered applications with LLMs and modern AI frameworks

• Familiarity with LLM internals, prompt engineering, RAG architectures, and AI/ML principles

• Regular user of AI coding assistants with proven methods for AI-enhanced development

• Experience with containerization, serverless architectures, and infrastructure-as-code

• Strong problem-solving skills; ability to work independently and ship fast with minimal direction

• Portfolio or examples of rapidly built prototypes or applications  

Preferred Qualifications

• Experience with fine-tuning LLMs and custom model training

• Experience in developing agentic AI systems and autonomous workflows

• AWS and/or Azure certifications (Solutions Architect, Developer, AI/ML Specialty)

• Experience with real-time applications, WebSockets, and streaming architectures

• Contributions to open-source AI/ML projects

• Experience in EdTech or learning technology industry

• Familiarity with MLOps practices and model deployment pipelines

• Full-stack development experience including modern frontend frameworks  

Key Competencies

• Velocity – Ships working code fast; optimizes for speed without sacrificing core quality

• Polyglot Approach – Comfortable across languages and platforms; picks up new tech quickly

• AI-Native Thinking – Instinctively brings to bear AI tools to amplify productivity and capabilities

• Full-Stack Versatility – Builds complete applications from infrastructure to UI

• Pragmatic Engineering – Makes smart tradeoffs; knows when "good enough" enables progress

• Self-Direction – Thrives with autonomy; doesn't wait for detailed specifications  

What We Offer

• High-impact R&D role building the future of AI at a leading learning company

• Freedom to work with brand new AI technologies and development tools

• Fast-paced, innovation-focused environment that values speed and experimentation

• Direct visibility with AI Enablement leadership

• Competitive compensation and comprehensive benefits

• Professional development and continuous learning opportunities

• Flexible remote/hybrid work arrangements  

Cengage is committed to working with broad talent pools to attract and hire strong and most qualified individuals. Our job applicants are considered regardless of race, national origin, religion, sex, sexual orientation, genetic information, disability, age, veteran status, and any other classification protected by applicable federal, state, provincial or local laws.  

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Cengage is also committed to providing reasonable accommodations for qualified individuals with disabilities including during our job application process. If you are an applicant with a disability and require reasonable accommodation in our job application process, please contact us at [email protected].  

About Cengage

Cengage, a global education technology company serving millions of learners, provides affordable, quality digital products and services that equip students with the skills and competencies needed to be job ready. For more than 100 years, we have enabled the power and joy of learning with trusted, engaging content, and now, integrated digital platforms. We serve the higher education, workforce skills, secondary education, English language teaching and research markets worldwide. Through our scalable technology, including MindTap and Cengage Unlimited, we support all learners who seek to improve their lives and achieve their dreams through education. 

Compensation

At Cengage Group, we take great pride in our commitment to providing a comprehensive and rewarding Total Rewards package designed to support and empower our employees. Click here to learn more about our Total Rewards Philosophy.

The full base pay range has been provided for this position. Individual base pay will vary based on work schedule, qualifications, experience, internal equity, and geographic location.  Sales roles often incorporate a significant incentive compensation program beyond this base pay range.

In this position,  you will be eligible to participate in the company’s discretionary incentive bonus program.  This position's bonus target amount, which is not guaranteed and is dependent on individual performance and overall company results among other factors, is provided below.