Are you looking to grab a job as a Machine Learning Engineer at Apple? Kudos, you landed on the right page.
This article is mainly focused on the position of Machine Learning Engineer at Apple. We will discuss the process, skill sets, and roadmap that will help you grab this dream job. We have also included some resources that will help you in your journey.
About Apple 🧐
Apple Inc. is an American multinational technology firm with headquarters in Cupertino, California that focuses on consumer goods, software, and online services. Apple is the world’s largest firm by market capitalization as of June 2022, the fourth-largest vendor of personal computers (PCs) by unit sales, and the second-largest producer of mobile phones. Apple is the greatest technology company by revenue (totaling US$365.8 billion in 2021). Along with Alphabet, Amazon, Microsoft, and Meta, it is one of the Big Five American IT firms.
Now, let us discuss the role of a Machine Learning Engineer at Apple with its roles and responsibilities, and a proper guide to crack the opportunity.
About the job📝
In the field of information technology, a machine learning engineer (ML engineer) is a specialist in the development of self-contained artificial intelligence (AI) systems that automate the usage of predictive models. The AI algorithms that define machine learning are designed and developed by machine learning engineers (ML).
Data scientists, data analysts, data engineers, and data architects are among the people that an ML engineer frequently collaborates with while working as a member of a broader data science team. Depending on the scale of the firm, they might also communicate with groups other than their own teams, such as the IT, software development, sales, or web development teams.
The IS&T team at Apple is looking for a machine learning expert to assist them in getting the most out of their collection of data. Data collection, cleaning, preprocessing, model training, and deployment to production are all responsibilities.
After the Job description, let’s move on to the Roles and Responsibilities of a Machine Learning Engineer at Apple.
Roles and Responsibilities
As a ML Engineer or Machine Learning Engineer at Apple, you will be responsible for:
Analyzing the Machine Learning algorithms that can be used to solve a given problem and also ranking them by their success probability.
Exploring and visualizing the data to gain a better understanding of it, then identifying the differences in the distribution of data that could affect performance when you deploy that model in the real world.
Verifying data quality and/or ensuring it via data cleaning.
Defining different validation strategies.
Defining the preprocessing or feature engineering that has to be done on a given dataset.
Training the models and tuning their hyper-parameters.
Analyzing all the errors of the models and designing strategies to overcome them.
Deploying the models to production.
After the roles and responsibilities, let’s move on to the Skills that are required for a Machine Learning Engineer at Apple.
Skills Required
If you want to become a Machine Learning Engineer at Apple, you must have:
Bachelor’s degree in Computer Science or equivalent with five years plus of relevant experience.
Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas.
Expertise in visualizing and manipulating big datasets.
After all, that, let’s move on to the Preparation Strategy that will help you in getting the role of Machine Learning Engineer at Apple.
Preparation Strategy
Most Machine Learning Engineers start by getting a Bachelors’s degree in Computer Science or any other related field.
Start learning Programming using Python and spend some time working on its libraries like NumPy, TensorFlow, MatPlotLib, etc.
After that, you can also learn to work on Database technologies.
It would be best if you studied scientific computing and analysis packages such as Scikit-learn, Pandas, and SciPy in depth.
You must also try to work on Linux Operating System.
For this role, one of the essential things is experience.
With all these, start working on your communication skills as well.
Career Map
Due to the fact that it allows machines to learn on their own and decreases the amount of work that must be done by humans, machine learning is immensely popular. As a result, there are numerous lucrative employment options in machine learning, including those for data scientists, Natural Language Processing scientists, and business intelligence specialists.
Data Scientist: The term “data scientist” refers to a person who gathers, analyses, and interprets vast volumes of data using advanced analytics tools like Machine Learning and Predictive Modeling to generate insights that may be put to use. The company’s leaders utilize these to decide on business decisions afterward.
NLP Scientist: Natural language processing, or NLP, is the practice of teaching robots to comprehend human language. This indicates that, ultimately, machines will be able to communicate with people in our language.
Business Intelligence Developer: A Business Intelligence Developer is one that uses Data Analytics and Machine Learning to gather, analyze and interpret huge amounts of data and produce actionable insights that can be used to make business decisions by the executives of the business.
Resources
Now, check out the given links. They will help you in your journey.
The salary of a Machine Learning Engineer or ML Engineer in India starts from ₹ 3,50,000 to ₹ 21,00,000 per year, which would make the average base salary be:
Average Annual Salary (/yr)
₹ 7,50,000 per year
Estimated Take Home Salary
₹ 55,661 - ₹ 57,055 per month
The average salary mentioned above is subject to change by Apple.
Link to Apply
You can apply for this job via the Apple Jobs portal using this link.
So, what are you waiting for?
Still nervous about the preparations? No issues. Practice makes the man perfect and confident! So why don’t you practice and gain some confidence? Check out the link that will help you to crack any interview😉👍.
In the end, it’s always you vs. you!
Frequently Asked Questions
Which is better, software engineering or machine learning?
Machine learning is more adaptable to complicated issues because of its intrinsic statistical character, but it is also more challenging to interpret and troubleshoot. The development of the machine learning application is more exploratory and iterative than software engineering.
What language do machine learning engineers use?
Python is the one that 57% of data scientists and machine learning developers use, and 33% prioritize it for development.
Is machine learning a stressful job?
However, as machine learning is a topic that necessitates extensive research for each project, an expert in the field must adhere to the conventional 9–5 timetable. As a result, you’ll spend half of your time studying something new and exciting. This makes working with machine learning fascinating and less demanding.
Does machine learning require coding?
Yes, some coding experience is mandatory if you actually want to work in the fields of artificial intelligence and machine learning.
Is IT hard to get a machine learning job?
Machine learning is a growing field getting a lot of attention, but getting machine learning jobs is still very difficult. Landing an engineering role at a big company means knowing not just Data Science but also things like programming and system design.
Conclusion
In this article, we have thoroughly discussed the Machine Learning Engineer at Apple. We hope that this article has helped you enhance your knowledge regarding the Machine Learning role at Apple and its preparation material as well as the process.
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