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salary information

Salary Information for a Machine Learning Engineering Management in United States

Median salary:

This data reflects Total Cash for a Level 3 Machine Learning Engineering Management at a mid-size company. To get more detailed information on total compensation for the role of Machine Learning Engineering Management 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 Engineering Management 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 Engineering Management 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. Selects, develops and retains team members to drive success of the team/department/function.

What are the characteristics of a level 3 Machine Learning Engineering Management?

A level 3 Machine Learning Engineering Management in United States works directly with senior management to drive company objectives and creatively achieve goals.

Machine Learning Engineering Management

Benchmark Role

Management

Job Type

Machine Learning

Job Family

Technology

Job Area

Quality of Life in the United States for a $200,175 Salary

Overview

A salary of $200,175 per year places an individual or household well above the median income levels in the United States. This income allows for comfortable living standards in most regions, although the cost of living and home prices can significantly vary depending on the location.

Cost of Living

  • Varies by Region: Urban areas such as New York City, San Francisco, and Washington D.C. exhibit higher living costs, including housing, groceries, and transportation.
  • Comfortable Budget: In less expensive areas, this income allows for substantial savings, discretionary spending, and a higher standard of living.
  • Key Expenses: This salary comfortably covers major expenses such as housing, utilities, and personal expenses while allowing for savings and investments.

Housing Market

  • Affordability: In most parts of the U.S., $200,175 per year can purchase a high-quality home or afford comfortable rental accommodations.
  • Mortgage Eligibility: Eligible for substantial mortgage offerings, providing opportunities in both high-density urban settings and more spacious suburban areas.
  • Home Value Impact: Housing costs are significantly influenced by desired location, but this income generally supports homeownership aspirations.

Quality of Life

  • Discretionary Spending: Availability of funds for leisure activities, travel, dining, and cultural experiences.
  • Work-Life Balance: Possibility to afford services that improve work-life balance, such as housecleaning or childcare.
  • Savings and Investments: Substantial capacity to save for retirement, emergencies, or further investment opportunities.

Access to Healthcare

  • Insurance Premiums: This income level can cover comprehensive health insurance premiums, reducing out-of-pocket healthcare expenses.
  • Quality Care Access: Access to quality healthcare providers and services without significant financial strain.
  • Preventive Care: Ability to afford preventive services and elective procedures, enhancing long-term health prospects.

Quality of K-12 Schools

  • Public Education: Opportunity to reside in areas with superior public school systems.
  • Private Education: Financial capacity to consider private schooling if desired, supporting diverse educational environments.
  • Supplemental Education: Resources available for tutoring, extracurricular activities, and educational enrichment programs.

Summary

Living on a $200,175 salary in the United States affords a high quality of life, with significant advantages in terms of housing, healthcare, and educational opportunities. The variability in cost of living between urban and rural

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OpenComp aggregates multiple data sources to provide accurate salary data for United States, specifically for a Level 3 Machine Learning Engineering Management. 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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