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How Much Do Machine Learning Engineers Earn?

machine learning engineer

Machine learning Engineers’ salaries have been a topic of interest because of the recent expansion of AI. This has fueled a high demand for ML skills across various industries. According to Glassdoor, ML Engineers can expect starting salaries of $126,574, with more senior positions earning beyond $187,000.

The Bureau of Labor Statistics predicts an annual 1.8 percent rise in job opportunities in computer systems from 2022-2032, which includes roles for ML Engineers.

Additionally, the demand for AI talent in India is growing by around 15 percent, reflecting the global trend in the AI job market. These salaries reflect the significant skills gap and the fierce competition for talent in Machine Learning and AI.

To better understand salary ranges, this article guides you in negotiating your way to a successful Machine Learning Engineer Career.

Factors Affecting Machine Engineer Salary

Several factors can influence the salary of a machine learning engineer. These include the level of experience, education (such as having a master’s or Ph.D.), the specific role within the field (e.g., research scientist, data scientist, ML engineer), and the industry or company size. Let’s explore deeper into these factors.

Location and Industry

Salaries can also vary based on the location and industry. For example, salaries in high-cost-of-living areas like Silicon Valley tend to be higher compared to other regions. In addition, industries with a high demand for machine learning talent, such as tech companies or finance, may offer higher salaries than other sectors. MLOps professionals and exGooglers involved in influential projects like BERT and GPT-3 are considered highly skilled and have earned close to seven figures.

Experience and Education

Machine learning engineers with several years of industry experience and advanced degrees such as master’s or Ph.D. may command higher salaries than those with less experience or education. Salaries for ML research scientists vary, with recent graduates earning around $300,000 total compensation at Bay Area FAANG companies.

Job Market

The job market for machine learning engineers can fluctuate based on trends and demand. There is a strong demand for skilled machine learning practitioners, but staying updated on industry trends and developments is essential.

Individual Circumstances

Factors such as specific job responsibilities, company size, benefits, stock options, and work-life balance should also be considered when assessing the overall compensation package.

Gender Pay Gap

Unfortunately, the gender pay gap still exists, with women making, on average, 77% of what a man makes in the same position, which can affect salaries for female engineers.

Industries Hiring Machine Learning Engineers

Industries Hiring Machine Learning Engineers

Industries such as manufacturing and finance and large tech companies like Google are examples of tech companies hiring machine learning engineers. The shift to prioritize engineers who understand ML over a traditional standalone data scientist role indicates a widespread need across technology-driven sectors.

According to recent reports, the following industries show a high demand for machine-learning skills:

Manufacturing 

In manufacturing, machine learning is used for predictive maintenance, optimization of supply chains, and improving manufacturing processes.

Healthcare

The healthcare sector employs machine learning for drug discovery, personalized medicine, and to enhance diagnostic accuracy.

Finance

Financial institutions use machine learning for fraud detection, algorithmic trading, and risk management.

Automotive 

The automotive industry hires ML engineers to develop autonomous systems and improve vehicle safety features.

Telecommunications

In telecommunications, machine learning is used for network optimization, predictive maintenance, and customer analytics.

Energy

Energy sector companies use machine learning for demand forecasting and optimizing energy distribution.

Salary Comparison by Location

Salary Comparison by Location

How much do machine learning engineers earn, The salaries of machine learning (ML) engineers vary depending on their location due to differences in factors such as cost of living, demand and supply dynamics, industry concentration, economic conditions, and government policies. 

Cities with high living costs, such as San Francisco and New York City, typically offer higher salaries to compensate for living expenses. Areas with a strong demand for ML talent and a limited supply may also offer higher wages.

Moreover, regions with a concentration of tech companies or research institutions provide competitive salaries to attract and retain skilled professionals. 

Economic conditions and government incentives also impact salary levels, with stronger economies and favorable policies typically correlating with higher wages for ML engineers. Here is a brief overview of how much different major cities across the globe pay ML Engineers:

San Francisco, USA

San Francisco, home to Silicon Valley, has a high concentration of tech giants, startups, and venture capital firms driving innovation in machine learning and artificial intelligence. 

Due to the high demand for machine learning professionals from companies like Google, Facebook, and Tesla and the city’s exorbitant cost of living, skilled professionals receive exceptionally high salaries to attract and retain them. The average salary for a machine learning engineer in San Francisco is $179,965 per year.

New York City, USA

New York City is a thriving tech hub, particularly in the finance, media, and advertising industries that rely heavily on data-driven technologies. The city’s diverse economy and high cost of living lead to competitive salaries for machine learning engineers in finance, e-commerce, and other sectors. In New York, the average annual salary for a machine learning engineer is $186,131.

London, UK

London is a popular destination for Machine Learning (ML) talent due to its strong position as a global financial hub and a thriving startup ecosystem. The city boasts a vibrant tech scene offering sought-after opportunities in finance, healthcare, and e-commerce industries. Despite London’s relatively high cost of living, competitive salaries are offered to ML Engineers, with an average annual salary of £99,413.

Toronto, Canada

Thanks to its rapidly growing startup ecosystem and diverse economy, Toronto has become a prominent technology hub in North America. Compared to Silicon Valley, the city offers a lower cost of living and strongly emphasizes AI research and development. This translates to competitive salaries for Machine Learning engineers, particularly in sectors such as finance, healthcare, and autonomous vehicles. In Toronto, the average annual salary for a Machine Learning Engineer is $118,618.  

Berlin, Germany

Berlin has a thriving startup scene that attracts Machine Learning (ML) engineers due to its comparatively affordable cost of living compared to other European tech hubs. The city has gained a reputation as a hub for AI innovation, and this, along with demand from industries such as e-commerce, gaming, and transportation, has led to competitive salaries for tech talent. The estimated total pay for a Machine Learning Engineer is €71,051 per year in Berlin, Germany.

Paris, France

Paris boasts a thriving tech ecosystem with a strong emphasis on AI and machine learning. The city’s global cultural and economic significance and government initiatives promoting innovation have resulted in competitive compensation packages for ML engineers in the finance, healthcare, and aerospace industries. The average annual salary for a machine learning engineer in Paris, France, is €48,726, while the gross salary averages €82,922.

Experience-Based Salary Breakdown

Experience-Based Salary Breakdown

In general, the salary of a machine learning engineer varies depending on their years of experience. Usually, entry-level ML engineers with 0-2 years of experience earn lower salaries due to their limited knowledge and skills.

As ML engineers gain more experience (2-5 years), their salaries increase as they become more proficient in machine learning techniques and gain practical experience in applying them to real-world problems. Mid-level ML engineers (5-8 years) command higher salaries as they demonstrate their expertise in developing and deploying complex ML models, often leading teams or projects.

Senior ML engineers (8+ years) earn the highest salaries because of their extensive experience, leadership abilities, and ability to drive innovation and solve challenging problems. 

Salaries are offered based on these experience levels to attract and retain talent, reflecting the value and expertise engineers bring to organizations at each stage of their career progression. Let’s take a detailed look at the salaries of ML engineers based on their experience level.

Entry-Level Salaries 

For entry-level machine learning engineers, it typically starts at around $ 69,362. However, starting salaries can be significantly higher in high-demand areas or at top companies.

Mid-Level

With a few years of experience, machine learning engineers can expect to see their salaries grow. The average salary for a machine learning engineer is around $99,000. Still, with additional experience, salaries can range to $180,000 or more.

Senior-Level

Senior machine learning engineers with extensive experience and specialized skills can command salaries that exceed $140,180.

In some cases, particularly in high-demand sectors or at leading tech companies, these salaries can reach as high as $350,000.

Online Courses for Machine Learning Engineers

Numerous online courses are offered to people who wish to become machine learning engineers. These courses cater to different levels of competence and preferences in learning, from basic concepts to practical skills and issues in machine learning. Coursera, Udacity, Udemy, and edX are some of the most popular.

For those at entry-level, Coursera courses like “Machine Learning by Andrew Ng” provide a strong foundation on the fundamentals of ML. This course covers linear regression, neural networks, and deep learning.

Similarly, “Introduction to Machine Learning for Coders” by fast.ai is a hands-on approach appropriate for programmers.

Intermediate learners can access classes such as “Deep Learning Specialization,” available on Coursera, or “Machine Learning Engineer Nanodegree,” provided by Udacity. They further cover advanced topics like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and natural language processing (NLP).

Advanced learners who want specialization can choose among offerings, including “Advanced Machine Learning Specialization” on Coursera or “Deep Reinforcement Learning Nanodegree” from Udacity. Such courses deal with the latest trends, such as reinforcement learning or generative adversarial networks (GANs).

Kaggle and GitHub also offer hands-on opportunities by participating in competitions and contributing to open-source projects. These online courses provide flexibility in terms of pacing and accessibility, making them ideal for self-paced learning and skill development in the field of machine learning.

Conclusion

Machine learning jobs hold immense promise for those looking for a bright career with great salaries and job opportunities across the globe. On average, starting salaries are around $100,000, but experienced professionals can earn well beyond $300,000. 

With the demand for machine learning engineers increasing in various industries, staying updated with the latest industry trends and acquiring the necessary skills through online courses and practical projects is essential. 

The factors that affect salaries, such as location, experience, and industry demand, help you negotiate better compensation packages for a fulfilling career in machine learning.

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