Free ATS Resume Checker for AI Engineers
Recruiters hiring AI engineers look for Python, hands-on work with LLMs and frameworks such as LangChain or Hugging Face, and evidence that you shipped something people use - not just a demo. Upload your resume to see how it reads, which AI engineering skills it shows, and what to improve before you apply.
By uploading, you agree to our Terms and Privacy Policy. Your CV is saved to a RoleMapr profile under the email in it, and that profile is visible to recruiters - even before you create an account.
Skills recruiters look for in AI Engineer resumes
These are the skills RoleMapr looks for when it reads a AI Engineer resume. Include the ones you have actually used - and show where you used them, not just in a skills list.
- Machine Learning
- Deep Learning
- NLP
- REST APIs
- Python
- SQL
- PyTorch
- TensorFlow
- Hugging Face
- Transformers
- LLMs
- Prompt Engineering
- LangChain
- LangGraph
- RAG
- Vector Databases
- Pinecone
- FAISS
- ChromaDB
- OpenAI API
- Gemini API
- Claude API
- Fine-tuning
- Model Evaluation
- FastAPI
- Docker
- Kubernetes
- AWS
- Azure
- GCP
- MLflow
- Git
What to highlight at your experience level
Fresher / 0-2 years
Show one or two working projects - a RAG chatbot over real documents or an LLM-powered tool - with a link to the code and a note on how you checked answer quality. Solid Python and API basics matter more than a long list of frameworks.
2-5 years
Show LLM or ML features you took to production - the use case, how you evaluated outputs, and how you handled latency, cost and failures. Mention the stack you deployed on, such as FastAPI, Docker and a cloud provider.
5+ years
Show architecture decisions - when you chose RAG, fine-tuning or a smaller model, how you set up evaluation and guardrails, and how you worked with product and security teams. Mention engineers you guided.
Common AI Engineer resume mistakes
- Calling a single LLM API call an "AI platform". Interviewers will ask what you built around it, so describe it honestly.
- No mention of evaluation. Saying how you measured answer quality or reduced wrong answers sets you apart from tutorial projects.
- Leaving out the software engineering side - APIs, testing, deployment and monitoring are a big part of AI engineer roles.
- Listing every new framework and model name. Keep the tools you actually used and can explain in an interview.
- Putting project links or skills inside images, headers or footers. ATS tools may not read them, so keep them in the main text.
Weak vs strong resume bullet points
The strong versions say what you did, with which tool, and what changed because of it.
Weak: Built a chatbot using LangChain and OpenAI.
Strong: Built a RAG assistant over 2,000 internal policy documents using LangChain, a vector database and an LLM API, answering HR questions with source links for about 600 employees.
Weak: Worked on prompt engineering.
Strong: Created a test set of 300 real support queries and used it to compare prompts and retrieval settings, choosing the version reviewers rated most accurate before launch.
Weak: Deployed AI models.
Strong: Packaged an LLM classification service with FastAPI and Docker on AWS, adding caching and rate limits that kept responses under 2 seconds and kept API costs in budget.
Find AI Engineer jobs that match your resume
RoleMapr collects jobs from company career pages and recruiters, ranks them by how well they match your resume, and shows which skills you are missing.
Create a free accountFrequently asked questions
What is the difference between an AI engineer and an ML engineer resume?
An AI engineer resume usually focuses on building applications with LLMs and existing models - RAG, agents, retrieval design, evaluation and deployment. An ML engineer resume leans more towards training, tuning and serving custom models and the pipelines behind them. Many roles overlap, so match the wording of the job description.
Can a fresher get an AI engineer job in India?
Yes, though many openings ask for some experience. Freshers have the best chance with strong Python, one or two deployed GenAI projects with public code, and internships. A software engineering role with AI features is also a good first step.
Is this resume checker free?
Yes. You can upload your resume and see the results without creating an account. If you sign up later with the same email, the full report and your job matches are saved to your profile.
What does the checker look at?
It reads your resume the way an ATS and a recruiter would: the role it fits, your experience level, the skills it finds, and how clearly your work and results come across. You get strengths and areas to improve.
What happens to my resume after I upload it?
It is saved to a RoleMapr profile under the email in your resume, and that profile is visible to recruiters looking for candidates. We email that address a link to remove it at any time. See our Privacy Policy for details.