Machine learning jobs has been considered as one of the most sought after jobs by most industries. The job role such as ML engineer offers lucrative salary packages with a promising career.
The machine learning field is one of the fastest-growing domains in the current technology industry.
According to Indeed, a machine learning engineer has topped to be one of the best jobs in 2019 with a growth of 344 percent.
Let us further delve deeper into the trending tech occupations in machine learning.
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Machine learning engineer
The job role: An ML engineer is solely responsible for designing and implementing new machine learning algorithms and collaborate closely with the product development teams. The individual must also implement open source and proprietary algorithms in order to handle and process the data. AI/ML engineers, and machine learning specialists are also expected to conduct data modeling and data. evaluation. The majority of these engineers are responsible for building efficient and self-learning applications by conducting statistical analysis and then fine-tuning using the test results. Their job description is also to train and retrain the systems whenever necessary.
Key skills:
- Statistics and mathematics
- Probability
- Programming skills (R, Python, and Java)
- Data structures, data modeling, and software architecture
- Algorithms
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Data Scientist
The job role: It is said that almost 93 percent of the data scientists are involved in data cleaning and data modeling. Their job responsibility is to make reliable and proper use of the data given to them and then positive future insights are forecasted based on the past data and the current data collected. As per a survey by Analytics India Magazine and other researches, Python has been voted as the most used and preferred programming language by data scientists. It was also found more than 75 percent of these respondents mentioned Python to be one of the major programming languages to help them get a job in the data science industry.
Key skills:
- Mathematics and statistics
- Machine learning algorithms
- Programming skills such as R and Python
- Deep Learning and Neural Networks
- Data visualization tools i.e. Tableau, ggplot
- Databases i.e. SQL
- Business acumen
- Problem-solving skills
- Storytelling
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Computational Linguist/NLP Engineer
The job role: Ever since the 1960s, computers were majorly used for language teaching. However, we’re now experiencing voice recognition, speech to text, and many other applications used in our daily lives due to machine learning. Even so, the computers can learn spoken languages via computational linguistics with the help of patterns in the speech. As such, the job role of a computational linguist or an NLP engineer is to work on such applications.
Other applications are based on the automated scoring of non-native responses such as TOEFL and GRE. Mobile-based learning applications such as Duolingo. Grammar checkers like Grammarly, and computer-assisted spoken language tutoring such as elsaspeak.com.
Key skills:
- Extensive skills in syntax, spelling, and grammar
- Machine learning skills
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Human-centered Machine Learning Designer
The job role: In machine learning, you will find a division that handles the machine learning algorithms revolving around humans called the human-centered machine learning. The job role of a human-centered machine learning designer majorly involves creating a pattern based on the data available so that the machine learns accordingly based on the information given.
For instance, YouTube suggests videos based on user history. Well, if the examination is done based on the human-centered perspective, human behavior can easily be designed by building workflows by exploring the co-adaptation of humans, systems, and human working practices.
Key skills:
- Programming skills (R, Python, and Java)
- Machine learning skills
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Software Engineer or a Software Developer in Machine Learning and AI
The job role: Strong coding skills are required so that the software engineer skilled in AI or ML will be able to build machine learning algorithms. Their core job and responsibility includes creating flow charts, drawing models and diagrams, and documenting the systems.
