Career as a Machine Learning Engineer in the post-pandemic world | Adamas University

Career as a Machine Learning Engineer in the post-pandemic world Engineering & Technology

Career as a Machine Learning Engineer in the post-pandemic world

The entire globe has been facing an unprecedented challenge from the Novel Coronavirus, which has made the physical world come to a standstill and the world economy has been holding onto a thread due to this fatal pandemic. But the brighter side of this gloomy situation is that companies are finally appreciating and understanding the significance of Machine Learning and Artificial Intelligence in the practical world. More and more brands are now taking up Machine Learning solutions for their business problems. Not only Machine Learning is used to combat the global pandemic but it has also come out as an important tool in constructing a better world post-COVID. Machine Learning has the capability of providing an understanding and early analysis of problems and prompt resolutions. This technology is used by the doctors and health practitioners to track the virus, identify potential threat to patients and predict the possible cure from disease. These reasons indicate that Machine Learning and Artificial Intelligence, both are here to rule and this can be an interesting career option for the aspirants who are passionate about data and numbers. Machine Learning has been at the forefront for all the advanced programmers who intend to develop intelligent systems that learn and apply knowledge. These programmers, better known as Machine Learning (ML) engineers, train systems with the help of complex datasets and algorithms.

Machine learning brief explanation

Machine Learning is a subset of Artificial Intelligence, which combines Statistics and Computer Science to predict using different mathematical models. The predictive model can be based on like whether an image contains cat or dog, predicting credit card fraud detection etc. The main objective of Machine Learning is to take decisions based on predictive modelling. Hidden patterns across the datasets are extracted and useful insights about data are found out to drive important decisions, improve customer relationship based on feedback patterns or launch new business.

What are the pre-requisites for becoming a Machine Learning engineer?

A Machine Learning engineer requires to be proficient in a bunch of technical skills for building predictive models.

Below are given some of the primary components of the Machine Learning engineer role:

  • Data: The Machine Learning engineer has to understand the importance of data in predictive modelling. The data pre-processing is one of the important steps for constructing a Machine Learning model. Data has to be analysed and described in terms of the problem requirement. Good quality data is a necessary requirement in building efficient Machine Learning model.
  • Predictive Models: Machine Learning engineers need to construct the models designed by the data scientists, understand the model validation in order to get an essence of the estimation of value addition to the business and understand how to fine-tune these models to optimize them for the consumption by end users.
  • Software Engineering: They need to be efficient in coding back-end so that the models can be made available to users through a user-friendly API.
  • Efficient Scaling of Infrastructure: They need to keep the system prepared for scaling of infrastructure so that the system may not collapse when multiple number of users start operating their models.

Where is Machine Learning used in real life?

Machine Learning is being used in real life in many fields, industries or domains. Some of the application areas of Machine Learning are listed below:

  • Image Recognition: It is a popular and widely used application area of Machine Learning. This is used to identify an object from a digital image.

Some of the use-cases of Image Recognition:

  • Photograph-tagging in social media
  • Hand-writing recognition by segregating a single letter into component images
  • Speech Recognition: Machine Learning has the capability of translating speech into text.

Some of the use-cases of Speech Recognition:

  • Voice-based digital assistants like Amazon Alexa or Google Home etc.
  • Search based on voice
  • Dialling based on voice
  • Symptom analysis in healthcare domain: Machine Learning can help the medical practitioners to ascertain symptoms in diseases by leveraging the capability of chat bots. This is called symptom analysis which utilises the power of Natural Language Processing and text mining etc. to analyse the disease symptoms and predict the next steps to be taken as precautionary measures or remedial measures.

Primary objectives of a Machine Learning Engineer

Primary responsibilities of a Machine Learning engineer lies in creation of Machine Learning models and re-training models as and when required. Some of the common responsibilities of the role relate to:

  • Machine Learning system design
  • Implementation of Machine Learning algorithms and tools
  • Dataset selection and dataset representation methods
  • Verification of data quality
  • Accomplishing statistical analysis
  • Executing Machine Learning tests
  • Improving Machine Learning models by tuning of models by proper selection of hyper-parameters
  • Constructing Machine Learning apps as per requirement

Now, let us see the skill sets that are important for a Machine Learning Engineer.

Skill set of a Machine Learning Engineer

For becoming a Machine Learning Engineer, an aspirant should have the following skills:

  • Mathematical and statistical skills relating to subjects such as Calculus, Linear Algebra, Statistics etc.
  • Advanced degree in Computer Science, Mathematics, Statistics or a related degree
  • Master’s degree is desirable in Machine Learning, Deep Learning or related fields
  • Coding in programming languages like Python, R etc.
  • Skills pertaining to Software Engineering, Computer Architecture, Data Science and the like
  • Working experience with Machine Learning packages and libraries etc.

References:

  1. Rise in the demand for Machine Learning & AI skills in the post-COVID world, https://timesofindia.indiatimes.com/spotlight/rise-in-the-demand-for-machine-learning-ai-skills-in-the-post-covid-world/articleshow/75464397.cms
  2. Machine learning engineer (ML engineer), https://www.techtarget.com/searchenterpriseai/definition/machine-learning-engineer-ML-engineer#:~:text=Machine%20learning%20engineers%20design%20and,data%20engineers%20and%20data%20architects.
  3. AI/ML Remains The Most In-Demand Tech Skill Post COVID, https://analyticsindiamag.com/ai-ml-remains-the-most-in-demand-tech-skill-post-covid/
  4. AI, Automation and In-Demand Skills for a Post-Pandemic World, https://www.sigconsult.com/blog/2021/03/ai-automation-and-in-demand-skills-for-a-post-pandemic-world?source=google.co.in
  5. Artificial Intelligence in a post-pandemic world of work and skills, https://www.cedefop.europa.eu/en/news/artificial-intelligence-post-pandemic-world-work-and-skills

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