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MACHINE LEARNING

Top 5 Product-Based Companies for Machine Learning Engineers

Machine learning is what’s currently backing up most of our daily tech today, that’s how much influence and reliability it has garnered over the last few years. It has emerged as a game-changer for businesses across various industries, driving vital changes and bringing about quite the tech revolution.

As a result, a growing number of product-based companies are adopting ML to enhance their operations, deliver personalized experiences, and gain a competitive edge in the market. And what it leads to is the constant rise in demand for skilled ML professionals.

With so many great companies and opportunities out there, it can be pretty overwhelming to find the right fit for you. So, to make it a tad bit easier we will dedicate this article to discussing some great product-based companies for machine learning engineers out there, along with what they offer.

Table of contents


  1. The top 5 product-based companies for machine learning Engineers:
    • 1) Amazon
    • 2) Facebook (Meta)
    • 3) Google
    • 4) Apple
    • 5) Uber
  2. Concluding Thoughts…
    • Which company is leading in machine learning?
    • What companies pay machine learning engineers the most?
    • Why are ML engineers paid so much?
    • Does Amazon use machine learning?

The top 5 product-based companies for machine learning Engineers:

1) Amazon

Amazon career page
Source: Amazon jobs

Ranked #5 among the Most Innovative Companies in the world by Forbes, Amazon is a global leader in e-commerce and cloud computing. And I’m sure you’ve experienced firsthand how major their focus is on customer experience.

Hence, Amazon has integrated machine learning across its vast array of services, from the recommendation engine hinting you towards the exact kind of products you might be interested in, to multiple live data statistics that garner trust from customers.

Amazon’s machine-learning applications are diverse and impactful. For example, the Alexa Smart Home Devices utilize natural language processing and machine learning algorithms to understand and respond to user commands. How exciting does that sound! Now imagine being a part of building something like this on a day-to-day basis, just wow.

At Amazon, you are to be challenged (in a good way) every day! Hence, it’s a no-brainer that it ranks number one on our list of the top product-based companies for machine learning engineers.

  • Company Strength: 15,41,000 (2022)
  • Net Revenue: $513.98 Billion
  • No of Openings in India(in 2023): 500+
  • Link to Apply for Jobs: Amazon
  • Salary offered to machine learning engineers: up to 14 LPA

Make sure you understand machine learning fundamentals like Python, SQL, deep learning, data cleaning, and cloud services before we explore them in the next section. You should consider joining GUVI’s Machine Learning Career Program, which covers tools like Pyspark API, Natural Language Processing, and many more and helps you get hands-on experience by building real-time projects.

Also, if you want to explore Python through a Self-paced course, try GUVI’s Python Self-Paced course.

2) Facebook (Meta)

Meta career page
Source: Meta Careers

We’ve all been with Facebook ever since its inception, following along with all the exciting social media advancements and wondering how they even do this!

Facebook has amassed an enormous amount of user data. To make sense of this data and deliver a personalized user experience, it heavily relies on machine learning algorithms.

One of the most prominent applications of machine learning at Facebook is the News Feed algorithm. This algorithm analyzes user preferences, interactions, and content to curate a personalized feed for each user.

Facebook is constantly exploring new ways to utilize machine learning, including natural language processing, sentiment analysis, and content recommendation systems.

And it’s FACEBOOK! Need I say more? Getting a job here would truly be like every techie’s dream come true, but it is competitive so buckle up and master machine learning, a great resource would be this IIT-M Pravartak certified Machine Learning Career Program with top industry mentors and extensive placement assistance!

  • Company Strength: 86,482 (Dec, 2022)
  • Net Revenue: 11,660.9 crores USD (2022)
  • No of Openings (in 2023): 50+
  • Link to Apply for Jobs: Meta
  • Salary offered to data engineers: up to 40 LPA
MDN

3) Google

Google career page
Source: Google Careers

We all know this one, we’ve basically grown up with Google and seen all of its expansions with YouTube, Meet, Docs, and so much more. All techies have at some point wondered and even dreamed of what it would be like to work at Google, that’s at the very epicenter of innovation in tech.

Machine learning is at the core of Google’s operations, powering everything from search algorithms to voice recognition systems.

Google’s machine learning applications are diverse and far-reaching. For instance, Google Assistant utilizes natural language processing and machine learning to provide personalized responses and assistance to users.

Google’s machine-learning capabilities also extend to image recognition, language translation, and self-driving cars.

By combining vast amounts of data with powerful machine learning algorithms, Google continues to push the boundaries of what is possible in the realm of technology and artificial intelligence. Imagine working in an environment like that!

  • Company Strength: 178,234 (Jan 2023)
  • Net Revenue: $279.8 Billion
  • No of Openings (in 2023): 1,264
  • Link to Apply for Jobs: Google
  • Salary offered to machine learning engineers: up to 56.9 LPA

4) Apple

Apple career page
Source: Apple

Oh, haven’t we all desired an Apple at some point? The sleek phone has earned quite a reputation for itself(pretty overhyped if you ask me). But IOS, that’s what actually makes it worthwhile for me.

The software is just so user-friendly and the most important part… it is very private and secure, which is very difficult to have in this highly social world. And how are these amazing features made possible? Machine Learning!

One of the most notable applications of machine learning at Apple is our very own Siri. Siri utilizes natural language processing and machine learning algorithms to understand user requests and provide relevant information and assistance.

With its commitment to user privacy and seamless integration of machine learning, Apple offers machine learning engineers an opportunity to work on innovative projects that impact millions of users worldwide. You get to be one with many tech revolutions and earn quite a salary!

  • Company Strength: 164,000 (2022)
  • Net Revenue: $20 Billion 
  • No of Openings (in India,2023): 82
  • Link to Apply for Jobs: Apple
  • Salary offered to machine learning engineers: up to 54 LPA

5) Uber

As a leader in the ride-hailing industry, Uber has revolutionized transportation with its innovative platform. Machine learning plays a pivotal role in Uber’s operations, enabling efficient matching of drivers and passengers, optimizing routes, and predicting rider demand.

Uber’s machine learning algorithms analyze vast amounts of data, including historical trip data, traffic patterns, and user preferences, to make real-time decisions and enhance the user experience. Machine learning is also utilized in Uber’s dynamic pricing model, which adjusts prices based on supply and demand.

With its focus on data-driven decision-making and continuous optimization, Uber offers machine learning engineers the opportunity to work on cutting-edge projects that shape the future of transportation.

  • Company Strength: 32,800 (2022)
  • Net Revenue: $31.8B (2022)
  • No of Openings (in India,2023): 20+
  • Link to Apply for Jobs: Uber
  • Salary offered to machine learning engineers: up to 15 LPA

Concluding Thoughts…

Product-based companies are at the forefront of leveraging machine learning to drive innovation and transform industries. And we’ve discussed all that you would need to know about the top dogs in the game!

Working at these product-based companies for machine learning engineers offers an exciting opportunity to contribute to groundbreaking projects, collaborate with top experts in the field, and make quite the buck.

Keep working hard because it is sure to reward you in more ways than one when you achieve your goal of working for one of these dream companies. Good Luck!

Which company is leading in machine learning?

As discussed above Google, Microsoft, Amazon, and Facebook (now Meta) are some of the top dogs in the ML game. These tech giants make significant investments in AI research and development, leading in various aspects of machine learning.

What companies pay machine learning engineers the most?

Google, Facebook, Apple, and Amazon are known for offering some of the highest salaries to machine learning engineers which we have discussed in depth in the article above.

Why are ML engineers paid so much?

Well, there are a few prominent reasons. To begin with, the demand for their skills is soaring as ML is integral to various industries. Second, there’s a shortage of qualified professionals.

Additionally, ML projects are complex and require expertise so not everybody can handle them. Lastly, the potential for high returns on ML investments justifies the substantial salaries.

MDN

Does Amazon use machine learning?

Yes, Amazon extensively employs machine learning in various aspects of its operations. ML enhances its customer experience through recommendation algorithms, improves supply chain management, and streamlines logistics.

Amazon’s voice assistant, Alexa, also relies heavily on ML for natural language processing and the list goes on and on. ML is everywhere!

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  1. The top 5 product-based companies for machine learning Engineers:
    • 1) Amazon
    • 2) Facebook (Meta)
    • 3) Google
    • 4) Apple
    • 5) Uber
  2. Concluding Thoughts…
    • Which company is leading in machine learning?
    • What companies pay machine learning engineers the most?
    • Why are ML engineers paid so much?
    • Does Amazon use machine learning?