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Amazon AI Engineer Resume Examples

Photo of Brenna Goyette
Brenna Goyette
Certified Professional Resume Writer, Career Expert

Updated 9 min read

This article will provide an overview of what to include in a resume when applying for a position as an AI Engineer at Amazon. It will explain the skills and experience needed, and how to highlight your past accomplishments that make you a strong candidate for the role. Additionally, it will provide tips on how to craft compelling descriptions of your work history and educational background that demonstrate why you are the best person for the job.

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Amazon AI Engineer Resume Example

Teaira Borbor, AI Engineer

teaira.borbor@gmail.com

(589) 143-4952

Charlotte, NC

Professional Summary

I am an AI Engineer with over 3 years of experience in developing machine learning models and algorithms. I have a proven track record in developing AI applications for various industries including healthcare, finance, and retail. My skills include data engineering, software engineering, machine learning, deep learning, and natural language processing (NLP). I am highly experienced in deploying and managing ML models in production environments and have experience in developing custom ML pipelines for large-scale data collection, preprocessing, and feature engineering. Additionally, I have a strong understanding of AI/ML architectures, optimization techniques, and deployment strategies. I am passionate about developing AI solutions that improve efficiency and effectiveness.

Work Experience

Lead AI Engineer at IBM Watson, NC

Dec 2022 - Present

  • Developed an AI-powered analytics platform for IBM Watson that improved customer satisfaction ratings by 20%, resulting in a 50% increase in revenue.
  • Led the design and implementation of new machine learning algorithms, reducing error rates from 15% to 5%.
  • Spearheaded development on two projects related to natural language processing (NLP) systems which increased accuracy levels up to 95%.

Senior AI Engineer at SAS Institute, NC

Jul 2020 - Oct 2022

  • Developed an AI-driven analytics platform that increased customer satisfaction by 15% and reduced operational costs by $1.2 million over the course of 12 months: Utilized advanced machine learning algorithms to develop a predictive model for SAS Institute’s existing data sets, resulting in improved accuracy and efficiency across all departments.
  • Led team effort to create natural language processing (NLP) application for web search queries which resulted in 20X faster response times than competitors: Leveraged knowledge on NLP technologies such as deep neural networks, tokenization techniques, sentiment analysis models etc., developed custom coding scripts using Python programming language & successfully deployed them into production environment with 0 downtime or errors reported.
  • Implemented computer vision system capable of analyzing images from satellite imagery at scale – reducing manual labor hours required per task from 10 days to 2 minutes : Designed complex architecture leveraging Convolutional Neural Networks (CNN), OpenCV libraries while also applying various image augmentation methods like scaling/flipping/rotations etc.; ensuring high level accuracy & reliability through extensive testing process before deploying it live within organization's infrastructure framework.

Education

Bachelor of Science in Artificial Intelligence Engineering at North Carolina State University, Raleigh, NC

Aug 2015 - May 2020

Relevant Coursework: Algorithms & Complexity, Machine Learning, Computer Vision, Natural Language Processing, Robotics, Data Structures & Algorithms.

Skills

  • Machine Learning
  • Data Science
  • Programming
  • Algorithm Design
  • Natural Language Processing (NLP)
  • Deep Learning
  • Computer Vision

Certificates

  • IBM AI Engineering Professional Certificate
  • AWS Certified Machine Learning - Specialty

Tips for Writing a Better Amazon AI Engineer Resume

1. Highlight Your Experience: Make sure to include any relevant experience you have in AI engineering, such as past projects or research papers. Be sure to include the technologies and tools you used for each project.

2. Showcase Your Achievements: Include any awards or recognitions you received related to your AI engineering work. This will help show potential employers that you are a dedicated and capable engineer.

3. Use Action Words: To make your resume stand out, use strong action verbs when describing your achievements and skills. Examples of action words include “developed”, “implemented”, and “analyzed”.

4. Include Keywords: Employers often look for specific keywords when they scan resumes, so be sure to include any relevant keywords related to AI engineering in your resume. This will help increase the chances of your resume being noticed by recruiters and hiring managers.

5. Proofread Your Resume: Before submitting it, double-check for spelling mistakes or typos in your resume so that employers can take you seriously as a professional AI engineer

Related: Machine Learning Engineer Resume Examples

Key Skills Hiring Managers Look for on Amazon AI Engineer Resumes

The use of Applicant Tracking Systems (ATS) by companies like Amazon makes it more important than ever for applicants to incorporate keywords from the job description into their resumes and cover letters. ATS scan applications for keywords relevant to the job posting and rank them accordingly, so it is essential that AI Engineer applicants use terms from the job description like “machine learning”, “neural networks”, and “data mining” in order to increase their chances of being considered for the role.

The following list includes common skills and key terms associated with AI Engineer positions at Amazon.

Key Skills and Proficiencies
Machine LearningNeural Networks
Deep LearningData Science
Natural Language Processing (NLP)Computer Vision
Image ProcessingPattern Recognition
Algorithm Design & AnalysisPython Programming
TensorFlowScikit-Learn
KerasProbability & Statistics
Reinforcement LearningRobotics
Big Data TechnologiesAutomation
Cloud ComputingDistributed Systems
Data Mining & ModelingArtificial Intelligence (AI)

Related: Machine Learning Engineer Skills: Definition and Examples

Common Action Verbs for Amazon AI Engineer Resumes

Finding the right action verbs to use on a resume can be difficult, especially when trying to create an Amazon AI Engineer Resume. It is important to use varied action verbs in order to stand out and give your resume a unique edge. Using the same words over and over again can make your resume seem dull and lack creativity. To create an effective Amazon AI Engineer Resume, look for words that describe activities related to AI engineering such as designing, developing, coding, testing, optimizing and deploying. Additionally, you should also include words that demonstrate your technical skills such as analyzing data sets and building machine learning models. By using these types of action verbs on your resume, you will be able to effectively showcase your experience in the field of AI engineering.

To give you an advantage in the job search process, we've compiled a list of powerful action verbs that can help boost your resume and increase your chances of securing an interview:

Action Verbs
DevelopedImplemented
DesignedConfigured
ProgrammedTested
MonitoredAnalyzed
OptimizedAutomated
InvestigatedResolved
TroubleshotDebugged
DocumentedMaintained
UpgradedDeployed
IntegratedCustomized
EvaluatedStreamlined

Related: What does a Machine Learning Engineer do?

Editorial staff

Photo of Brenna Goyette, Editor

Editor

Brenna Goyette

Expert Verified

Brenna is a certified professional resume writer, career expert, and the content manager of the ResumeCat team. She has a background in corporate recruiting and human resources and has been writing resumes for over 10 years. Brenna has experience in recruiting for tech, finance, and marketing roles and has a passion for helping people find their dream jobs. She creates expert resources to help job seekers write the best resumes and cover letters, land the job, and succeed in the workplace.

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