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Selected role

AI ML Engineer R D

Cengage US

$101k - $163k Senior Full-time

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.

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.

10% Annual: Individual Target

$101,900.00 - $163,000.00 USD

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