Machine learning engineering has become one of the most in-demand and highly compensated careers in tech. As more companies adopt machine learning techniques to analyze data, make predictions, and automate tasks, there is a growing need for technical professionals who can build, optimize, and maintain machine learning systems. In this blog post, we'll take a look at what a machine learning engineer does and examine the lucrative salaries these professionals can command.

How Much Do Machine Learning Engineers Make?

According to statistics from jobs site Glassdoor, the median pay for machine learning engineers in the United States is $240,705 per year. Total compensation including bonuses, stock options, and profit sharing can push salaries even higher.

Data scientists at top tech companies can earn a wide range of salaries, depending on their level of experience and seniority.

• At Google, data scientists at the L3 level earn an average of $155,000 per year. As they move up the ranks, their salaries can increase to as much as $2.6 million per year at the L7 level.
• Amazon data scientists earn an average of $168,500 per year at the entry-level. Their salaries can go up to $1.2 million per year at the most senior levels.
• Apple data scientists earn a similar range of salaries, with entry-level salaries starting at around $175,000 per year and top salaries reaching $1.3 million per year.
• Facebook(Meta) data engineer salaries levels from IC3-IC9. IC3 data engineers typically make around $230k, and IC5 data engineers make around $311k. In these positions, base salaries range around $150k-190k with stock and bonuses.

These salaries are based on data from Levels.fyi, a website that collects salary information from tech workers. It is important to note that these are just averages, and the actual salaries of data scientists can vary depending on a number of factors, such as their location, company, and experience.

Salaries also vary significantly based on factors like location, years of experience, and specific industry. For example, machine learning engineers make an average of 160,000 in tech hubs like San Francisco and Seattle where talent is highly concentrated. Senior-level engineers with 5+ years of experience can expect to earn total compensation packages north of $200,000. Industries with massive quantities of data like finance and e-commerce tend to pay ML engineers the highest premiums.

Some examples of different levels of machine learning engineer salaries

Machine learning expertise pays extremely well, especially for engineers who combine it with software engineering and data engineering skills. With demand for ML engineering talent showing no signs of slowing down, salaries are likely to rise even higher in the coming years.

What is a Machine Learning Engineer?

A machine learning engineer is responsible for developing and optimizing machine learning algorithms and systems. Their primary duties include:

• Collecting, cleaning, and labeling datasets to train machine learning models
• Selecting appropriate machine learning algorithms and techniques
• Building and optimizing machine learning pipelines and workflows
• Monitoring model performance and retraining models as needed
• Developing machine learning applications and services for use in products and systems
• Collaborating with data scientists to identify business cases for machine learning and prototype solutions

It's a highly technical role that requires expertise in machine learning frameworks like TensorFlow and PyTorch, as well as strong software engineering skills.

Factors Influencing ML Engineer Salary

The salary of a Machine Learning Engineer is influenced by several factors, including:

1. Experience: Entry-level engineers typically earn less than mid-career professionals. For example, a Machine Learning Engineer with 5-7 years of experience can earn an average salary of $141,720 or above.
2. Location: Salaries can vary significantly by city due to differences in the cost of living. For instance, the average Machine Learning Engineer salary in the United States is $161,526 per year, but it can range from $104,454 to $246,329, and the average salary in Detroit, Michigan is $126,116.
3. Skill Sets: Certain skills may offer better pay, and acquiring more experience in machine learning can lead to a higher salary1.
4. Industry: The industry in which a Machine Learning Engineer works can also affect their salary. For instance, those working in leadership roles or high-paying industries may earn more.
5. Company: The specific company and the position within the company can also impact salary.

Why is There So Much Demand for Machine Learning Engineers?

Machine learning has become a key competitive advantage for many tech companies and a must-have capability for enterprises in every industry. As a result, there simply aren't enough qualified candidates to meet the surging demand. The shortage of talent is even more pronounced when it comes to engineers who possess both machine learning expertise and software engineering abilities. This supply-demand imbalance creates lucrative opportunities for those entering the field.

In addition, machine learning engineering is an extremely challenging and fast-moving field. New frameworks and techniques emerge constantly, requiring engineers to continuously learn and master new skills. Engineers who can keep up with innovations in the field and quickly apply them to real-world problems are highly sought after.

Conclusion

Machine learning engineering is one of the most lucrative and future-proof careers available for tech professionals today. The soaring demand for ML engineers, combined with the limited supply of qualified candidates, leads to generous salaries often exceeding $200,000 for experienced professionals. For software developers looking to level up their skills and earning potential, focusing on machine learning is a wise choice. With continuous learning and the right mix of capabilities, the financial upside for machine learning engineers is impressive.