- What should your AI engineer resume include?
- How can you create a professional summary?
- How should you describe your work experience as an AI engineer?
- How to include a fitting AI engineer resume education and certifications section?
- Which key skills are relevant for an AI engineer resume?
- How to select the most impactful AI engineer resume template
- Copyable AI engineer resume example
- Key takeaways for writing an AI engineer resume
Looking for your next AI engineering role? You need a resume that’s as intelligent as the systems you build. This AI engineer resume example and writing guide will show you how to create an AI engineer resume that gets you an interview.
Artificial intelligence (AI) engineers build solutions to solve problems. When applying for an AI engineering job, your resume needs to show prospective employers exactly what you can do. We’ll show you how to create a targeted, professional AI engineer resume that gets you noticed.
This resume guide, along with our AI engineer resume example, will discuss these topics:
What to include on an AI engineer resume
How to describe your work experience and education
The best skills to include on your resume
How to select the right resume template for an AI engineer
What should your AI engineer resume include?
Your AI engineer resume should highlight your technical expertise and problem-solving abilities. Hiring managers want to know about your experience with machine learning models, data processing, and AI frameworks. Your resume should showcase your standout ability to build and deploy AI solutions that solve problems or improve operations for businesses.
Include these elements on your resume for an AI engineer position:
A resume header with your contact information
How can you create a professional summary?
As the AI field becomes more competitive, your resume needs to stand out. A memorable professional summary can get a recruiter’s attention and move your resume forward.
In two or three sentences, summarize your experience and proficiencies with different tools and technologies. For example, you could highlight your knowledge of AI frameworks like TensorFlow, PyTorch, and JAX.
Your summary should also showcase your top career achievements. Think about projects where you’ve contributed to notable business outcomes, such as lower operational costs or improved efficiency. These accomplishments show potential employers how they can benefit from hiring you.
Check out our adaptable AI engineer resume summary example below:
Experienced in developing, deploying, and optimizing AI/ML models for large-scale production systems with a strong foundation in deep learning, natural language processing, and computer vision. Proficient in designing AI infrastructure, building scalable data pipelines, and implementing cloud-based machine learning solutions using frameworks such as TensorFlow, PyTorch, and JAX. Skilled in software engineering best practices, containerization, and distributed computing to ensure AI model stability, security, and efficiency. Adept at implementing ethical AI principles, including explainability, fairness, and bias mitigation, while ensuring robust monitoring and security of AI systems. Strong ability to collaborate cross-functionally, mentor junior engineers, and articulate technical concepts to non-technical stakeholders.
Expert Tip
Tailor your resume summary
Consider where you are applying and tailor your resume’s professional summary to match the role and the company.
For example, if you’re applying at a tech startup, you might focus on your ability to adapt quickly, wear multiple hats, and help with different technical projects. The goal is to show an employer why you’re a good fit for the specific role.
How should you describe your work experience as an AI engineer?
Your work experience section should tell the story of your growth and impact as an AI engineer. Instead of describing the duties you’ve had in previous jobs, focus on the solutions you’ve built and the problems you’ve helped solve.
List your experience in reverse chronological order, starting with your most recent role. Provide your job title, employer’s name, and employment dates for each role. Below this information, write concise bullet points that show the outcomes of your work.
When possible, quantify your bullet points using percentages, dollar amounts, or other metrics. This data proves you can deliver tangible, real results for companies.
Here’s an example of a bullet point with quantifiable data:
“Leveraged user feedback and real-time data to improve chatbot accuracy by 18% through advanced natural language processing techniques.”
View our adaptable AI engineer resume work history section below:
Senior AI Engineer at GE Healthcare, Boston, MA 2021 - Present
Developed and deployed AI models for automating clinical tasks using large-scale medical datasets, leveraging deep learning frameworks such as PyTorch and TensorFlow.
Built robust AI pipelines, integrating model training, fine-tuning, and deployment into cloud environments such as Azure and AWS.
Designed and optimized machine learning algorithms for natural language processing and medical imaging applications, ensuring compliance with healthcare regulations.
Contributed to the development of AI software solutions with reusable components, enabling scalable deployment across multiple teams.
Improved model inference speed by 30% through hyperparameter tuning and quantization techniques.
Developed a large-scale AI training pipeline, reducing model training time by 40% using distributed computing.
Led the implementation of ethical AI frameworks, enhancing model explainability and bias mitigation strategies.
Optimized AI-based medical imaging analysis, increasing diagnostic accuracy for clinical applications.
AI Engineer at Tech Solutions, Inc., San Francisco, CA 2018 - 2021
Designed, trained, and deployed AI models to solve complex business challenges, focusing on natural language processing, computer vision, and time-series forecasting.
Developed end-to-end machine learning workflows, optimizing performance and integrating AI solutions into enterprise systems.
Built and maintained APIs for AI models, ensuring seamless integration with existing applications.
Utilized cloud computing platforms to scale model training and inference while ensuring cost efficiency.
Participated in code reviews, architectural discussions, and continuous AI system improvement.
Deployed a real-time anomaly detection model, reducing fraud detection errors by 25%.
Created an automated ML pipeline, cutting data preprocessing time by 50%.
Implemented advanced prompt tuning techniques, enhancing response accuracy in AI-driven chatbots.
Designed a transformer-based NLP model, improving text classification accuracy by 18%.
Collaborated with data engineers to develop scalable data pipelines for AI-driven insights.
Machine Learning Engineer at InnovateAI Labs, Austin, TX 2016 - 2018
Assisted in building and training deep learning models for research and production, focusing on image recognition and natural language processing.
Conducted data preprocessing, augmentation, and feature engineering to improve model performance.
Supported the development of scalable AI solutions, working closely with senior engineers on deployment strategies.
Performed extensive model evaluation and fine-tuning, ensuring alignment with business objectives.
Contributed to technical documentation, maintaining best practices for reproducibility and scalability.
Optimized data augmentation techniques, increasing model generalization by 15%.
Researched and integrated state-of-the-art AI methodologies, improving model performance.
Developed a proof-of-concept AI solution, later adopted for full-scale deployment.
How to include a fitting AI engineer resume education and certifications section?
Companies typically prefer to hire AI engineers with a relevant degree, such as computer science or machine learning. Along with your formal education, this section can also list any certifications you’ve earned in the field.
Follow these tips for writing your resume education section:
Keep it simple. You only need to list the name of your degree and your field of study, such as a Bachelor of Science in computer science. If you have multiple degrees, the highest one should be listed first.
Mention coursework or projects. If you have limited professional experience, consider expanding your education section with the coursework or projects you’ve done in school. For example, classes in data structures and algorithms show employers that you have experience in these areas.
Highlight your certifications. Mention any certifications you have in relevant areas, such as AI frameworks or solutions. These credentials show you’re committed to staying current in this fast-paced field.
Master of Science in Artificial Intelligence at the University of California, Berkeley, Berkeley, CA
Bachelor of Science in Computer Science at the University of Texas at Austin, Austin, TX
Deep Learning Specialization – Coursera (Andrew Ng)
AWS Certified Machine Learning – Specialty
Microsoft Certified: Azure AI Engineer Associate
Certified Kubernetes Administrator (CKA)
Which key skills are relevant for an AI engineer resume?
AI engineers should have a range of technical skills. Outline your proficiencies in areas such as programming languages, data preprocessing, and machine learning algorithms. You can also include a few soft skills, such as problem solving or critical thinking.
The job description will provide guidance about the ideal skills to include on your resume. By using the same words or phrases, your resume has a better chance of passing an applicant tracking system (ATS), which scans resumes for specific keywords. (For more information about mastering the ATS, read our article on resume ATS optimization.)
Some good skills for an AI engineer resume might include:
Computer vision
AI deployment and infrastructure
Cloud computing
How to select the most impactful AI engineer resume template
Before an employer even reads your resume, they’ll notice the layout and design. Choose a resume template that’s clean, modern, and professional. This type of design makes it easy for a hiring manager to review your qualifications.
Your resume should have clear section headings to guide the reader. Use white space and bullet points to improve readability. Avoid using bold colors, large graphics, or other artistic elements that can overwhelm the hiring manager.
In most cases, your AI engineer resume should be no longer than one page. If you’ve worked in the field for over 10 years, you can use a second page to capture all of your relevant experience.
If you want to build your resume quickly, explore the different templates we offer in our career.io resume builder. Find one that matches your professional brand and experience. You can also get creative ideas by browsing the over 100 available resume examples.
Copyable AI engineer resume example
Summary example
Experienced in developing, deploying, and optimizing AI/ML models for large-scale production systems with a strong foundation in deep learning, natural language processing, and computer vision. Proficient in designing AI infrastructure, building scalable data pipelines, and implementing cloud-based machine learning solutions using frameworks such as TensorFlow, PyTorch, and JAX. Skilled in software engineering best practices, containerization, and distributed computing to ensure AI model stability, security, and efficiency. Adept at implementing ethical AI principles, including explainability, fairness, and bias mitigation, while ensuring robust monitoring and security of AI systems. Strong ability to collaborate cross-functionally, mentor junior engineers, and articulate technical concepts to non-technical stakeholders.
Employment history example
Senior AI Engineer at GE Healthcare, Boston, MA 2021 - Present
Developed and deployed AI models for automating clinical tasks using large-scale medical datasets, leveraging deep learning frameworks such as PyTorch and TensorFlow.
Built robust AI pipelines, integrating model training, fine-tuning, and deployment into cloud environments such as Azure and AWS.
Designed and optimized machine learning algorithms for natural language processing and medical imaging applications, ensuring compliance with healthcare regulations.
Contributed to the development of AI software solutions with reusable components, enabling scalable deployment across multiple teams.
Improved model inference speed by 30% through hyperparameter tuning and quantization techniques.
Developed a large-scale AI training pipeline, reducing model training time by 40% using distributed computing.
Led the implementation of ethical AI frameworks, enhancing model explainability and bias mitigation strategies.
Optimized AI-based medical imaging analysis, increasing diagnostic accuracy for clinical applications.
AI Engineer at Tech Solutions, Inc., San Francisco, CA 2018 - 2021
Designed, trained, and deployed AI models to solve complex business challenges, focusing on natural language processing, computer vision, and time-series forecasting.
Developed end-to-end machine learning workflows, optimizing performance and integrating AI solutions into enterprise systems.
Built and maintained APIs for AI models, ensuring seamless integration with existing applications.
Utilized cloud computing platforms to scale model training and inference while ensuring cost efficiency.
Participated in code reviews, architectural discussions, and continuous AI system improvement.
Deployed a real-time anomaly detection model, reducing fraud detection errors by 25%.
Created an automated ML pipeline, cutting data preprocessing time by 50%.
Implemented advanced prompt tuning techniques, enhancing response accuracy in AI-driven chatbots.
Designed a transformer-based NLP model, improving text classification accuracy by 18%.
Collaborated with data engineers to develop scalable data pipelines for AI-driven insights.
Machine Learning Engineer at InnovateAI Labs, Austin, TX 2016 - 2018
Assisted in building and training deep learning models for research and production, focusing on image recognition and natural language processing.
Conducted data preprocessing, augmentation, and feature engineering to improve model performance.
Supported the development of scalable AI solutions, working closely with senior engineers on deployment strategies.
Performed extensive model evaluation and fine-tuning, ensuring alignment with business objectives.
Contributed to technical documentation, maintaining best practices for reproducibility and scalability.
Optimized data augmentation techniques, increasing model generalization by 15%.
Researched and integrated state-of-the-art AI methodologies, improving model performance.
Developed a proof-of-concept AI solution, later adopted for full-scale deployment.
Education example
Master of Science in Artificial Intelligence at the University of California, Berkeley, Berkeley, CA
Bachelor of Science in Computer Science at the University of Texas at Austin, Austin, TX
Deep Learning Specialization – Coursera (Andrew Ng)
AWS Certified Machine Learning – Specialty
Microsoft Certified: Azure AI Engineer Associate
Certified Kubernetes Administrator (CKA)
Skills example
Machine Learning & AI Development: TensorFlow, PyTorch, JAX, MLX, Scikit-learn, NumPy, Pandas, OpenAI API, LangChain, Hugging Face Transformers
Software Engineering & Cloud Computing: Python, C++, Java, SQL, NoSQL (MongoDB, Firebase), AWS SageMaker, Azure ML, Google Vertex AI, Apache Spark, Hadoop, Dask, Git, Jenkins, MLflow
AI Deployment & Infrastructure: Docker, Kubernetes, Model Drift Detection, Explainable AI, Bias Mitigation, CI/CD Pipelines, API Development, Microservices Architecture
Key takeaways for writing an AI engineer resume
An AI engineer resume should focus on your technical skills and experience building AI solutions that solve problems.
Describe the outcomes of your past roles and projects with measurable data, such as accuracy rates, to show your impact as an AI engineer.
Include skills and keywords found in the job description to pass an applicant tracking system and capture the hiring manager’s attention.
Choose a clean, modern resume template and keep your resume to one page, unless you have many years of experience.
