Principal Machine Learning Engineer Salary at Consumeraffairs.Com Inc BETA

How much does a Consumeraffairs.Com Inc Principal Machine Learning Engineer make?

As of April 2025, the average annual salary for a Principal Machine Learning Engineer at Consumeraffairs.Com Inc is $142,799, which translates to approximately $69 per hour. Salaries for Principal Machine Learning Engineer at Consumeraffairs.Com Inc typically range from $125,832 to $158,008, reflecting the diverse roles within the company.

It's essential to understand that salaries can vary significantly based on factors such as geographic location, departmental budget, and individual qualifications. Key determinants include years of experience, specific skill sets, educational background, and relevant certifications. For a more tailored salary estimate, consider these variables when evaluating compensation for this role.

DISCLAIMER: The salary range presented here is an estimation that has been derived from our proprietary algorithm. It should be noted that this range does not originate from the company's factual payroll records or survey data.

ConsumerAffairs.com Inc Overview

Website:
consumeraffairs.com
Size:
200 - 500 Employees
Revenue:
$10M - $50M
Industry:
Media

ConsumerAffairs is a "managed marketplace" for life's hardest purchases. Our mission is to help consumers make smart buying decisions in moments of need. Every month, millions of people turn to ConsumerAffairs for help with their considered (often emotional), need-based purchases, and we connect hundreds of thousands of them directly to brands. These brands use our SaaS tools to manage their reviews and presence on ConsumerAffairs, communicate with potential customers and clients and generate revenue.

See similar companies related to Consumeraffairs.Com Inc

What Skills Does a person Need at Consumeraffairs.Com Inc?

At Consumeraffairs.Com Inc, specify the abilities and skills that a person needs in order to carry out the specified job duties. Each competency has five to ten behavioral assertions that can be observed, each with a corresponding performance level (from one to five) that is required for a particular job.

  1. Machine Learning: Using mathematical models, data, and algorithms to help a computer learn without direct instruction.
  2. Data Science: Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is the same concept as data mining and big data: "use the most powerful hardware, the most powerful programming systems, and the most efficient algorithms to solve problems". Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand and analyze actual phenomena" with data. It employs techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, and information science. Turing award winner Jim Gray imagined data science as a "fourth paradigm" of science (empirical, theoretical, computational and now data-driven) and asserted that "everything about science is changing because of the impact of information technology" and the data deluge. In 2015, the American Statistical Association identified database management, statistics and machine learning, and distributed and parallel systems as the three emerging foundational professional communities.
  3. Algorithms: Algorithms act as an exact list of instructions that conduct specified actions step by step in either hardware- or software-based routines.
  4. AWS: Amazon Web Services, Inc. is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis.
  5. Python: Applying the concepts and algorithms of Python to design, develop and maintain software applications to comply with business requirements.

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Check more jobs information at Consumeraffairs.Com Inc

Job Title Average Consumeraffairs.Com Inc Salary Hourly Rate
2 Senior UX Designer $102,743 $49
3 Software Engineer $115,764 $56
4 Talent Acquisition Coordinator $53,208 $26
5 Team Manager $47,296 $23
6 Technology Lead $126,405 $61
7 Accountant $84,420 $41
8 Assistant Store Manager $47,269 $23
9 Barista and Server $23,464 $11
10 Business Intelligence Architect $120,859 $58
11 Chief Executive Officer $792,094 $381
12 Compliance Consultant $90,025 $43
13 Content Marketing Specialist $69,043 $33

Hourly Pay at Consumeraffairs.Com Inc

The average hourly pay at Consumeraffairs.Com Inc for a Principal Machine Learning Engineer is $69 per hour. The location, department, and job description all have an impact on the typical compensation for Consumeraffairs.Com Inc positions. The pay range and total remuneration for the job title are shown in the table below. Consumeraffairs.Com Inc may pay a varying wage for a given position based on experience, talents, and education.
How accurate does $142,799 look to you?

FAQ about Salary and Jobs at Consumeraffairs.Com Inc

1. How much does Consumeraffairs.Com Inc pay per hour?
The average hourly pay is $69. The salary for each employee depends on several factors, including the level of experience, work performance, certifications and skills.
2. What is the highest salary at Consumeraffairs.Com Inc?
According to the data, the highest approximate salary is about $158,008 per year. Salaries are usually determined by comparing other employees’ salaries in similar positions in the same region and industry.
3. What is the lowest pay at Consumeraffairs.Com Inc?
According to the data, the lowest estimated salary is about $125,832 per year. Pay levels are mainly influenced by market forces, supply and demand, and social structures.
4. What steps can an employee take to increase their salary?
There are various ways to increase the wage. Level of education: An employee may receive a higher salary and get a promotion if they obtain advanced degrees. Experience in management: an employee with supervisory experience can increase the likelihood to earn more.