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salary information

Salary Information for a Machine Learning Engineer in United States

Median salary:

This data reflects Total Cash for a Level 3 Machine Learning Engineer at a mid-size company. To get more detailed information on total compensation for the role of Machine Learning Engineer in United States, including base pay, total cash, and equity by job level, region and company size, please join OpenComp.

25th percentile
50th percentile
75th percentile

Behind the numbers

What is the adjusted total comp for a Machine Learning Engineer in United States?

Total Comp (TC)
Cost of Living (COL) Index
COL-Adjusted TC
Median Home Price

Total Comp (TC)

Cost of Living (COL) Index
COL-Adjusted TC

Median Home Price

What are the responsibilities of a Machine Learning Engineer in United States?

Develop programs that will enable machines and systems that can learn and apply knowledge without specific direction. Match engineers who focus on artificial intelligence here.

What are the characteristics of a level 3 Machine Learning Engineer?

A level 3 Machine Learning Engineer in United States is a seasoned professional with competence, creativity in wide range of technical areas. They resolves most issues and problems effectively. Average experience 5.5 years.

Machine Learning Engineer

Benchmark Role

Individual Contributor

Job Type

Machine Learning

Job Family

Technology

Job Area

Quality of Life Assessment for a $169,915 Income in the United States

Overview

With an annual income of $169,915, an individual or household is positioned well above the median household income in the United States, which was approximately $68,700 in 2022. This higher income level allows for a comfortable lifestyle in many parts of the country, although experiences can vary significantly depending on the exact cost of living in different regions.

Cost of Living

  • Cost of Living Index: Many U.S. cities have a cost of living index over 100, meaning they are more expensive than the national average. Major urban centers such as New York City, San Francisco, and Los Angeles tend to have higher living costs.
  • Monthly Expenses: Key expenses include housing, groceries, transportation, healthcare, and utilities. A higher income allows for better management of these costs, even in more expensive areas.
  • Discretionary Spending: With this salary, there tends to be significant room for discretionary spending on entertainment, dining, travel, and savings.

Housing Market

  • Home Affordability: The median home price in the U.S. was approximately $428,700 in Q3 2023. A salary of $169,915 allows for easier affordability of homes, even in higher-cost areas.
  • Mortgage Capability: Assuming a good credit score, this salary enables the potential for substantial mortgage borrowing power, translating to diverse choices from urban apartments to suburban homes.
  • Rental Market: Renting is also a viable option, with the ability to afford high-end rentals in most markets or more luxurious spaces in less costly areas.

Quality of Life

  • Lifestyle Options: This income provides flexibility in lifestyle choices, including opportunities for travel, dining, and hobbies.
  • Savings and Investments: Adequate income to save substantially and invest for future goals like retirement, education, or other life aspirations.
  • Work-Life Balance: Depending on the job industry and required working hours, this income level might support a favorable work-life balance, aided by the ability to afford services such as childcare or housekeeping.

Access to Healthcare

  • Insurance Options: Individuals at this income level typically have access to comprehensive health insurance, often as a benefit of employment.
  • Healthcare Quality: Ability to afford high-quality healthcare providers and additional health services such as wellness and preventive care, which may not be fully covered

See salary information for the Machine Learning Engineer role elsewhere in the United States

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OpenComp aggregates multiple data sources to provide accurate salary data for United States, specifically for a Level 3 Machine Learning Engineer. The primary source is real-time, crowd-sourced salary information collected through direct integrations with hundreds of customer-connected HRIS platforms.

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