Machine learning is revolutionizing every industry, from healthcare to finance, manufacturing to entertainment. Consequently, the demand for experienced personnel to utilize machine learning has also increased. However, this newfound trend raises another question: what factors affect the machine learning engineer salary in the USA?

Unfortunately, as with most things in life, the answer is “It Depends.” However, the two major factors that impact a machine learning engineer salary in the USA are experience and location. Let’s take a closer look at how these factors can affect your salary.

How Do Location and Experience Affect Machine Learning Engineer Salary in USA?

Here’s how location and experience affect the machine learning engineer’s salary in the USA:

Location

The region heavily influences your potential income. You should not be surprised to discover that the most significant tech hubs, where the cost of living is usually high, are also the highest payers of salaries. It is reasonably logical: they should pay you more to afford living in the area. High costs of living are often justified by a generous paycheck which, in turn, reflects the effort of companies to hire the best employees in this highly competitive area. Here are some prime examples of top-paying USA locations for machine learning engineers, as per Glassdoor and Indeed:

1. San Francisco Bay Area: A perennial favorite at the top of our list, Silicon Valley hosts a plethora of tech titans (Google, Apple Inc., and Meta – formerly Facebook), all working to secure first access in signing ML talent. Salaries will be way over the national average.
2. Seattle: There’s Amazon and Microsoft. The tech world is thriving in this city, making it a great place for ML engineers with a handsome salary.
3. New York City: The Big Apple has a diverse tech ecosystem with financial, media, and technology giants like Google and Facebook offering wide career opportunities for developers. The salaries here are representative of the high cost of living.
4. Austin, Texas: A hotspot for tech companies and talent since it provides a lower-cost alternative to the coasts. Despite the good ML and AI job market growth there, Austin offers attractive salaries for an ML engineer.
5. Boston: Best for healthcare and biotech, Boston has a lot of opportunities in these areas for machine learning engineers. Higher-end salaries are equivalent to the higher end of pay in other major tech centers.

Experience

With millions of data science jobs, you have to realize that your experience is probably the most critical factor to bear in mind when talking about the machine learning engineer salary in the USA. More experience means that you are a more valuable candidate; consequently, companies are forced to offer you more money as an incentive to hire you. So, generally speaking, this is how experience impacts salaries:

1. Entry-Level (0-2 years): As a fresh graduate or someone with 1-2 years of experience, you can expect to make anywhere from $80k-$120k/year in the US (amount varies by location and tech stack). That is a solid foundation, but there are still many areas for improvement. For example, you could take Machine Learning course and upskill yourself. 
2. Experienced (3-5 years): Even with a handful of projects, you can still count on making $120,000 – $160,000 if you are seasoned in machine learning principles. This is where strong problem-solving skills and complex project handling come in handy.
3. Senior (5+ years): You receive $160k to well over $200k annually as a machine learning engineer who has ample experience and success with projects. With a few steps up, you move further and more to one side such that the level of your knowledge in some categorized area of machine learning can even increase your return.

Other Factors

Location and experience are the two biggest factors that drive salary, but they must be follow by:

1. Education: You might also consider earning a Master’s degree in computer science, statistics, or data science, which could make you more competitive and help with negotiating a higher starting salary.
2. Skillset: Expanding your skillset beyond core machine learning, such as cloud computing, big data tools, or even specific programming languages like Python or R, will boost your value by leaps and bounds. Consider taking machine learning courses too.
3. Employment Sector: The industry you work in can also play a part in how much money you make. Traditional companies adopting machine learning may not pay as much for talent compared to tech giants and cutting-edge startups.

How to Command Bigger Paychecks?

To maximize your earnings as a machine learning engineer, you should follow these tips:

1. Continuous Learning: Machine learning is an ever-changing field. Keep up to pace by taking online machine learning courses, including those from Interview Kickstart, or direct platforms offered by big tech companies like Google and Amazon.
2. Develop a Portfolio: What better way to get your foot in the door than having actual projects you have worked on or contributed to, even if they are personal? A strong portfolio showcases your talents to potential employers.
3. Community: Interact with other machine learning engineers online or at your local meetups. This way, you get to know about new opportunities and remain updated with industry trends as well.
4. Negotiate Your Salary: If you get a job offer, don’t shy away from negotiating your base pay. Check what the norm is for your experience level and location so you know if they are paying you correctly.

Conclusion

Now that you are equipped with how location and experience impact the Machine Learning Engineer salary in USA, work on your skills, take a machine learning course and be proactive in hunting for more jobs. This shall set you up well to have a successful career earning lucrative amounts of money as the surge towards the AI/ML domain continues. Keep in mind that the path to becoming a high-earning machine learning engineer involves hard work, continuous learning, and enthusiasm for the field.Launch your dream machine learning career with Interview Kickstart’s Machine Learning Course! Master the interview process with 500+ FAANG instructors, a data-driven curriculum, and live training sessions with mock interviews. Join the over 17,000 tech professionals who have taken their careers to the next level with Interview Kickstart’s Machine Learning Course. Register for our free webinar today and see how Interview Kickstart can help you land your dream job!