Deep Learning - Career Earnings Analysis (September 2025)

Colleagues, implementing a well-defined, forward-thinking career development plan can boost your career and income growth over a 30-year life cycle. According to Grand View Research “The global deep learning market size was estimated at USD $96.8 billion in 2024 and is projected to reach USD $526.7 billion by 2030, growing at a CAGR of 31.8% from 2025 to 2030. “ Making modest investments in your professional training and certification will reward you with greatly enhanced income potential.

Assumptions

• Duration: 30-year career lifecycle (e.g. age 25-55)

• Salary: $160,653/year - Indeed (compensation will vary by location - we will use a US average for our analysis)

• Education Level: This model is based upon the individual having a BS/BA degree. A MS/MA degree adds an extra 5%-10% to annual income

• Training & Certification: 5%-10% income lift/year

• Salary - Annual Increase per CPI Inflation: 2.5%/year

• Base Case: Junior Level - age 25/1st certification

• Intermediate Case: Senior Individual Contributor - age 30/2nd certification

• Advanced Case: Mid-Upper Management - age 35/3rd certification

• Expert Case: Technical Refresher - age 40-45/4th certification

Note: This income analysis does not include annual bonuses nor stock options.

Junior Level (5 years of experience)

• Title(s): Junior Deep Learning Engineer, AI/ML Intern (Deep Learning Focus), Deep Learning Research Assistant

• Base income: $186,197/year USD

• Sample Training & Certs: Introduction to Deep Learning, Deep Learning - Nanodegree Program

Intermediate (10 years of experience)

• Title(s): Deep Learning Engineer, Computer Vision Engineer, Natural Language Processing (NLP) Engineer, MLOps Engineer

• Base income: $225,412/year USD

• Sample Training & Certs: Deep Learning with TensorFlow, Deep Learning with TensorFlow & PyTorch, Deep Learning with Tensorflow, Keras and PyTorch 

Advanced (15 years of experience)

• Title(s): AI/DL Practice Manager, AI/ML/DL Vice President, AI/ML/DL Development Director, Senior Deep Learning Engineer, Deep Learning Solutions Architect, Applied Scientist (Deep Learning), Deep Learning Researcher

• Base income: $275,435/year USD

• Sample Training & Certs: TensorFlow Developer Professional Certificate, Machine Learning A-Z: AI, Python & R, 

Expert (Executive-Refresher) (20 years of experience)

• Title(s): AI/DL Consultant, Director of AI/Deep Learning, Principal Engineer/AI Fellow, Chief AI Scientist

• Base income: $449,774/year USD

• Sample Training & Certs: TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, 

Income Comparison

• Base Case: Junior Level - $186,197/year USD

• Intermediate Case: Senior Individual Contributor - $225,412/year USD

• Advanced Case: Mid-Upper Management - $275,435/year USD

• Expert Case: Technical Refresher - $449,774/year USD

Note: For a more comprehensive roster of Deep Learning certifications visit Coursera, DeepLearningAI, edX, InformIT, Udacity, Udemy, Google, IBM, Microsoft and Meta.

Deep Learning Specializations, Master Classes and Certifications

• Apply Generative Adversarial Networks (GANs)

• Data Structures, Algorithms, and Deep Learning Optimization

• Deep Learning A-Z 2025: Neural Networks, AI & ChatGPT

• Deep Learning - Nanodegree Program

• Deep Learning and Reinforcement Learning

• Deep Learning with PyTorch

• Deep Learning Specialization

• Deep Learning with TensorFlow

• Deep Learning with TensorFlow & PyTorch

• Deep Learning with Tensorflow, Keras and PyTorch

• Generative Deep Learning with TensorFlow

• Introduction to Deep Learning

• Machine Vision, GANs, and Deep Reinforcement Learning

• Machine Learning with Python: from Linear Models to Deep Learning

• Machine Learning A-Z: AI, Python & R

• Neural Networks and Deep Learning

• Structuring Deep Learning Projects

• TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

• TensorFlow Developer Professional Certificate

Get started today (teams & execs are welcome).

Recommended Reading: See the “Transformative Innovation” book series

 

1 - AI Software Engineer: ChatGPT, Bard & Beyond (Audible) (Kindle) 

2 - ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity (Audible) (Kindle)

3 - ChatGPT - The Era of Generative Conversational AI Has Begun (Audible) (Kindle) 

4 - The Race for Quantum Computing (Audible) (Kindle) 

5 - The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age  (Audible) (Kindle)

Much success in your Deep Learning career journey, Lawrence E. Wilson - AI Academy (share with colleagues & friends)

“ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Amazon Audible & Kindle book)

Friends, the new “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) (Kindle) book is the latest entry to the “Transformative Innovation” series. AI in all of its manifestations represents a bona fide “generational change” of human society as we know it. AI, like many of the historic innovations of the past, has the unsurpassed potential to impact the human race for both good and evil.  All humanity has a vested interest in ensuring the impact of AI is positive. The alternative is unfathomable: A dystopian environment leading to the destruction of mankind in a Noahic antediluvian episode of human culture by the hands of man himself or the divine, omnipotent hand of our sovereign Creator.

This book has a “5 Star” rating on Amazon. Reader comment “If you're curious about how AI works, how it's changing the world, and what might happen next, this book is great. It's a bit like a guide that helps you understand this complex topic. It's a journey that could open your mind to new ideas and change how you see the world.”

Table of Contents:

I - Introduction

II - The Birth of Artificial Intelligence (AI)

III - AI Research and Development

IV - The AI Quantum Multiplier

V - Technological Synergy

VI - The Ethics of Artificial Intelligence

VII - The Global Race for AI Supremacy

VIII - Understanding Artificial General Intelligence (AGI)

IX - Approaches to AGI Development

X - The Era of Artificial Superintelligence (ASI)

XI - Ensuring Safety in AGI and ASI

XII  - AGI and ASI Impact on Society and the Economy

XIII - AI Singularity (“Technological Singularity”)

XIV - Looking Beyond the Singularity

XV - Conclusions

Our journey will examine the birth of AI, the pending transition to Artificial General Intelligence, the era of Artificial Super Intelligence and thoughts on the possibility of AI (or “Technological”) Singularity. Although some of these topics have verifiable, concrete answers, overall, the pendulum rapidly swings from the domain of the known to the domain of the unknown and speculative in the concluding chapters. Our commitment is to amplify the known (factual) elements of Artificial Intelligence and only when necessary delve into the realm of the unknown (subjective) aspects of AI Singularity … and beyond.

Join us for a journey that will transform your thinking and possibly your life!

Order today:

Audible (https://tinyurl.com/3pswj5sx) 

Kindle (https://www.amazon.com/dp/B0CG536WDN)   

3 Book Series: “Transformative Innovation”: 

 

1 - ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity (Audible) (Kindle)

2 - ChatGPT - The Era of Generative Conversational AI Has Begun (Audible) (Kindle) 

3 - The Race for Quantum Computing  (Audible) (Kindle) 

Thank you for dropping a brief review on this book’s Audible or Kindle page.

Regards, Genesys Digital (Amazon Author Page) https://tinyurl.com/hh7bf4m9 

Machine Learning - Discover the Top 3 Career & Earnings Growth Strategies

Dev Colleagues, on average a Machine Learning Engineer earns $167k+ USD in the US according to Glassdoor. The first strategy is to Get Certified: A high quality credential from a reputable vendor or professional association can boost your income by 10%+. Topping our list is the popular Supervised Machine Learning: Regression and Classification program with some 814k students enrolled. Next is the Structuring Machine Learning Projects (481k enrollees). Third is the Convolutional Neural Networks program from DeepLearning.AI (526k enrolled). Second, Get Published: Write a series of posts or articles on Best Practices, Industry Trends and Emerging Technologies, and publish on DevPlan’s GCP portal, Medium, LinkedIn Articles, Reddit or Technology.org. Then reate a “project portfolio” on GitHub or LinkedIn that showcases your hands-on expertise. A high quality portfolio proves your expertise to future employers and gives you a competitive advantage over other job candidates. Then reate a “project portfolio” on GitHub or LinkedIn that showcases your hands-on prowess. A high quality portfolio proves your expertise to future employers and gives you a competitive advantage over other job candidates. And third, Get Connected: Professional networking and referrals are the most effective method for landing your dream job - within your current employer or at a new company (rather than simply applying for jobs online and standing in the Human Resources queue with the masses). Join and participate in 2-3 high profile groups or professional associations. Hugging Face is an excellent starting place. Consider the Machine Learning Society on LinkedIn. And explore Reddit’s Machine Learning sub-Reddit (2.9m members)

Get started today by enrolling in one or more training-certification programs:

• Convolutional Neural Networks 

• IBM Machine Learning Professional Certificate

• Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

• Machine Learning with Python

• Machine Learning Specialization

• Machine Learning with PyTorch

• Structuring Machine Learning Projects 

• Supervised Machine Learning: Regression and Classification 

Enroll today (teams & eces are welcome).

Success awaits you! Lawrence E. Wilson - AI Academy (share & subscribe)

Mathematics for Machine Learning Specialization

Colleagues, the “Mathematics for Machine Learning Specialization” you will build an intuitive understanding, and relating it to Machine Learning and Data Science. Training modules cover: 1) Linear Algebra - what linear algebra is and how it relates to data. Then we look through what vectors and matrices are and how to work with them, 2) Multivariate Calculus -  look at how to optimize fitting functions to get good fits to data. It starts from introductory calculus and then uses the matrices and vectors from the first course to look at data fitting, 3) Dimensionality Reduction with Principal Component Analysis - uses the mathematics from the first two courses to compress high-dimensional data. This course is of intermediate difficulty and will require Python and numpy knowledge. At the end of this specialization you will have gained the prerequisite mathematical knowledge to continue your journey and take more advanced courses in machine learning. Applied Learning Project: Through the assignments of this specialisation you will use the skills you have learned to produce mini-projects with Python on interactive notebooks, an easy to learn tool which will help you apply the knowledge to real world problems. For example, using linear algebra in order to calculate the page rank of a small simulated internet, applying multivariate calculus in order to train your own neural network, performing a non-linear least squares regression to fit a model to a data set, and using principal component analysis to determine the features of the MNIST digits data set.

Enroll today (teams & execs welcome): https://imp.i384100.net/APPX1N 

For your listening-reading pleasure:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 - “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) or (Kindle) 

3 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) or (Kindle) 

Much career success, Lawrence E. Wilson - AI Academy (share with your team)