How much does a Machine Learning Engineer make?
Machine learning engineers create systems that can learn and improve from data. This field has seen an increase in demand. With a wide range of experience, salaries for machine learning engineers vary. On average, these professionals earn around $188,873 a year. Here’s a closer look at the potential earnings:
Most machine learning engineers fall into the middle of the salary range. This range includes those with a few years of experience and solid skills. The lower end of this range starts around $70,000. For those with more experience and expertise, earnings can climb significantly. The top earners in this field can make over $300,000 annually. Job seekers with specific skills and a track record of success may see even higher salaries.
What are the highest paying cities for a Machine Learning Engineer?
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San Francisco, CA
Average Salary: $215,953
In San Francisco, tech giants like Google and Apple make this a vibrant hub for AI and machine learning. Working here often involves collaborating on cutting-edge projects and utilizing advanced tools to innovate in tech.
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Seattle, WA
Average Salary: $204,179
Seattle offers a dynamic tech scene with companies like Amazon and Microsoft leading the way. In this city, professionals focus on real-world applications of machine learning, contributing to significant advancements in cloud computing and AI.
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Los Angeles, CA
Average Salary: $191,511
Los Angeles is home to many entertainment and tech companies. Working here means applying machine learning to entertainment, marketing, and more. The diversity of projects keeps professionals engaged and motivated.
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San Jose, CA
Average Salary: $189,505
San Jose, the heart of Silicon Valley, boasts numerous tech firms like Intel and Cisco. Working as a machine learning expert here involves tackling complex problems and working with some of the brightest minds in tech.
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San Diego, CA
Average Salary: $178,824
In San Diego, companies like Qualcomm and Illumina offer exciting opportunities. Professionals here often work on health tech and wireless communications, using machine learning to drive innovation.
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Boston, MA
Average Salary: $178,758
Boston is rich in academic and tech talent. With institutions like MIT nearby, professionals here often engage with research and development, pushing the boundaries of machine learning.
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Austin, TX
Average Salary: $174,124
Austin is known for its vibrant startup scene and tech companies like Dell and IBM. Working here means being at the forefront of AI, with a strong focus on innovation and creativity in machine learning projects.
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Washington, DC
Average Salary: $173,064
Washington, DC, offers a unique blend of government and tech. Companies like IBM and various startups provide opportunities to apply machine learning to public sector challenges, combining tech with policy.
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Boulder, CO
Average Salary: $171,138
Boulder combines a laid-back lifestyle with a strong tech presence. Companies like Google and Tesla offer roles where professionals use machine learning to solve environmental and transportation issues.
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Ann Arbor, MI
Average Salary: $165,360
Ann Arbor is known for its academic institutions and tech startups. Here, professionals work on a variety of projects, from automotive tech to healthcare, making impactful contributions with machine learning.
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What are the best companies a Machine Learning Engineer can work for?
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Netflix
Average Salary: $488,679
Netflix offers exciting opportunities for Machine Learning Engineers in Los Gatos, California, and other locations. Here, you will work on projects that impact millions of users. The focus is on improving user experience through advanced ML models.
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Block
Average Salary: $293,263
Block provides roles for Machine Learning Engineers in San Francisco, California. The company is known for its innovative approach in the fintech sector. Working here means applying ML to develop secure and efficient financial solutions.
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Roblox
Average Salary: $290,974
Roblox, based in San Mateo, California, seeks Machine Learning Engineers to enhance user experience. The company is known for its immersive gaming platform. You will develop algorithms that make games more interactive.
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Whatnot
Average Salary: $279,597
Whatnot, located in New York, New York, offers Machine Learning Engineer positions. The company focuses on live shopping experiences. You will work on tools that analyze user behavior to improve sales.
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Pinterest
Average Salary: $274,837
Pinterest has openings for Machine Learning Engineers in San Francisco, California. The company is known for its visually driven platform. You will develop models that personalize user experience.
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Snap Inc.
Average Salary: $261,464
Snap Inc., based in Los Angeles, California, seeks Machine Learning Engineers. The company focuses on augmented reality. You will work on projects that enhance user engagement through AR.
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Zoom
Average Salary: $255,504
Zoom offers roles for Machine Learning Engineers in San Jose, California. The company is known for its video communication platform. You will develop models that improve communication efficiency.
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Scale AI
Average Salary: $245,953
Scale AI, based in San Francisco, California, seeks Machine Learning Engineers. The company focuses on data annotation for AI. You will develop models that improve data accuracy.
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Indeed
Average Salary: $245,462
Indeed has openings for Machine Learning Engineers in New York, New York. The company is known for its job search platform. You will develop models that improve job matching.
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ServiceNow
Average Salary: $243,687
ServiceNow, based in Santa Clara, California, seeks Machine Learning Engineers. The company focuses on workflow automation. You will develop models that improve workflow efficiency.
How to earn more as a Machine Learning Engineer?
Aspiring Machine Learning Engineers can increase their earnings by focusing on several key areas. Enhancing skills through continuous learning is crucial. Specialization in areas like deep learning, computer vision, or natural language processing can set a professional apart. Building a portfolio of projects demonstrates practical experience and can attract higher-paying opportunities.
Networking and staying active in the professional community can lead to better job offers. Attending conferences, participating in online forums, and contributing to open-source projects can build a reputation. Securing certifications from recognized organizations can also provide a competitive edge. These steps together can lead to higher salaries and more opportunities in the field.
Here are five factors to consider:
- Specialize in high-demand areas of machine learning
- Continuously update skills with the latest technology
- Build a strong portfolio of practical projects
- Engage in professional networking and community activities
- Obtain relevant certifications to validate expertise
