How Being a Machine Learning Engineer Can Be Rewarding in 2024?
Updated on Feb 04, 2025 | 8 min read | 5.5k views
Share:
For working professionals
For fresh graduates
More
Updated on Feb 04, 2025 | 8 min read | 5.5k views
Share:
Table of Contents
Machine Learning (ML) has grown exponentially in the last decade to become the most demanding technology for the next generation. ML, taken as a subset of Artificial Intelligence (AI), is used to develop systems or algorithms that can first learn from data, discover patterns and concepts from this information, and then plan or make decisions based on these learnings.
Today, researchers worldwide use machine learning in their applications across several verticals, such as agriculture, banking, marketing, search engines, linguistics, medical diagnosis, etc.
ML is a popular 21st-century career with unlimited scope and potential for next-generation as more and more organisations rely on data to scale their growth. Machine Learning Engineer is a term associated with a professional building career in this field. Many companies also use Machine Learning Scientists, software engineers, or ML experts in their job descriptions. As per Glassdoor, a person working as a Machine Learning Engineer in 2024 is earning on average $114,000 per year in the US with additional perks, bonuses, and more.
Machine Learning has different subsets, including Neural Networks, Natural Language Processing (NLP), and Deep Learning (DL). Many industry verticals are leveraging ML in various aspects to enhance their business prospects for the future.
Machine Learning has opened pandora’s box for technologies to learn and build sophisticated models. Here are some of the main possibilities that can have a significant impact on our life altogether:
Sentiments or emotions analysis from ML-based applications will help define the document’s tone or a customer review. This decision-making application will have the capability to realise the customer’s style by reading his review or any form and giving prediction based on its assessment.
Natural language processing (NLP) has also progressed rapidly in the last decade in building a communication link between the human language and computer. Some of the crucial hurdles in NLP are natural language generation, speech recognition, and understanding the natural language progression.
Get ML certification online from the World’s top Universities – Masters, Executive Post Graduate Programs, and Advanced Certificate Program in ML & AI to fast-track your career.
3. User Behaviour and Recommendations—Products and Movies
ML-based models are also used to study the changing trends and user behaviour corresponding to the market. Product recommendation is among the most successful applications of ML. Every year, we see new designs and changes in products. These ML models make the system understand behaviour based on different parameters such as timing, mood, seasonal, choice, reference, and many others.
Medical diagnosis is among the most advantageous possibilities for Machine Learning. Moreover, ML–AI in healthcare have proven their success in defining treatment protocol, personalised care, monitoring, and developing drugs. Predicting heart failure from exam reports and discovering patterns from cardiovascular records is gaining popularity in healthcare.
Most of the global companies are using Machine Learning in their IT architecture in several aspects—Pinterest for discovering unique and engaging content, Yelp for Image curation, Neural network in Google, Baidu Voice search, highly Intelligent CRMS at Salesforce, Ecommerce conversion at Edgecase, curated timelines at Twitter, Chatbots at Facebook, Netflix for recommending movies, Amazon for promoting products, etc.
At the latest, the World Health Organization (WHO) and Massachusetts Institute of Technology (MIT) used ML and AI to study and respond to Corona outbreaks to understand its spreading behaviour.
Machine Learning is continuously evolving as businesses are now shifting towards data and algorithms to study information. These study models are highly significant and shed insights into crucial factors in business growth. The global Machine learning market (ML), from its US$ projection of 8.43 billion in 2019, will increase at an alarming rate of 39.2% (CAGR) to US$ 117.19 billion by 2027.
Machine Learning Market Size and Growth: source
Machine Learning opens many career pathways for Data Science, Artificial Intelligence, Data Architect, Cloud Computing, Machine Learning as a Service (MLaaS), Big Data, and top executives level in organisations. With the rapid progress of deep learning in industries, several global companies are pushing their scope with ML and data analytics-driven solutions.
Some of the top MNCs for ML include IBM, Hewlett Packard (HP), Amazon Web Services (AWS), Google LLC, H2o.AI, Intel Corporation, Oracle Corporation, Microsoft Corporation, SAS Institute, Baidu, and more.
Today, Machine Learning has got integrated into more than 100 industries and counting. These aspects touch our lives daily and ease our decision-making capabilities. And with continuous research, this ML trend will further refine to build more sophisticated models for the future.
Global Machine Learning Market Share By Industry in 2019
The use of Machine Learning technology has significantly increased in the retail industry in the last few years. Today’s online platforms have incredible user experience with recommendation engines to add more visibility to their products or services. Visual search adds more credibility in reaching the desired results easier. Users can seamlessly upload the image to find their exact product, such as Google Lens and image search, Pinterest Lens Your Look, etc.
With modern economies changing user behaviour, machine learning algorithms help businesses in pricing strategies, offering discounts, and several cost optimisation techniques. ML-led systems have shown incredible success in predicting customer behaviour and giving them relevant offers to get more businesses conversions.
Machine Learning has shown remarkable success in the healthcare industry. Digital recording on smart devices helps medical professionals optimise proficiency, standardise decisions, and diagnose cancer elements in the human body with more accuracy and speed to get desired results. Various data and analytics models have come up in healthcare systems that add more reliability and trust.
Overall, ML-based algorithms have played a tremendous role in assessing diseases’ treatment and setting their protocols with long-term planning; several benefits have come from using ML–AI combination, including lower hospital stay, predicting chronic disease, lower mortality rate, analysing no show, lower readmissions, likely complication of conditions, and so on.
Personalisation is one of the main benefits that have come up with the integration of Machine Learning. Here are the essential roles Machine Learning is involved in concerning e-commerce industries:
Although ML requires a steep learning curve and continuous improvement, accompanied by a plethora of skills and education, it is a lucrative offer for the younger generation today. Professionals working as ML Engineers make huge earnings.
Here are the main reasons to choose Machine Learning Engineer in 2024 and have a chance at a bright future ahead:
Overall, Machine Learning in 2024 is one of the most rewarding careers with unmatched potential. Businesses today are pacing towards gaining a competitive advantage for the future. ML with deep learning, Data Analytics, and Artificial advantage are pillars of the next generation. So if you want to be the leaders of tomorrow, then Machine learning is your choice to be on one.
Even the current once-in-a-lifetime pandemic COVID situation has little impact on the demand for Machine Learning career opportunities. Machine Learning Engineer in 2024 jobs multiply, with industries shifting their focus towards this incredible technology ready for the futuristic challenges. With Machine Learning an essential part of Artificial Intelligence, you can expect ML to bring new opportunities and expand research areas to scalable heights.
If you’re interested to learn more about machine learning, check out IIIT-B & upGrad’s Executive PG Programme in Machine Learning & AI which is designed for working professionals and offers 450+ hours of rigorous training, 30+ case studies & assignments, IIIT-B Alumni status, & 10 practical hands-on capstone projects.
Get Free Consultation
By submitting, I accept the T&C and
Privacy Policy
Top Resources