Machine learning has become a rage of sorts in it the tech world. Owing to its diverse range of applications, machine learning jobs have sprouted in several industries. More and more conglomerates are employing machine learning models. This is so that they can better understand their customers. The healthcare industry, for instance, uses learning models in disease-detection and diagnosis as well as antibiotic research. Some other uses of machine learning are fraud detection and loan risk assessment in the banking sector. Today, several companies are offering capable engineers machine learning jobs!
Here’s a list of a few prominent machine learning jobs!
1. Core Machine Learning Engineer
Machine learning has become one of the most lucrative professions in the world. As of 2018, the average income of a machine learning engineer is INR 9,75,000. Even freshers start off with a neat sum of INR 6,82,000. A machine learning engineer needs to be well-versed in machine learning algorithms and deep learning architecture. If you want to deal with real-world uncertainties, you must have a good grasp of probability and statistics. Your job profile will include designing machine learning software programs for real-world application. Generally, the software that you will create will be a smaller component of the finalized product or service. But for that, you need to be well aware of the ecosystem your software will be a part of.
2. Machine Learning Researcher
Machine learning jobs include that of a researcher who work on to create novel machine learning techniques. As a machine learning researcher, you need to collaborate with other senior machine learning researchers. This is to bring into notice the supervised and unsupervised learning problems in a research environment where application is necessary. Your job would also involve the application of modern machine learning algorithms, neural networks and deep learning on real-world industrial data so you can build effective machine learning models, tailor-made for industries.
It’s true that the job of a machine learning engineer and a machine learning researcher might overlap. But there is a key difference – a machine learning engineer employs the techniques developed by a machine learning researcher.
3. Applied Scientist or Applied Machine Learning Engineer
An applied machine learning engineer is expected to have knowledge of machine learning, data mining as well as statistics. Knowledge of mathematics is an absolute must. Especially topics like Linear Algebra, Multivariate Calculus, Probability and Statistics as well as Numerical Optimization.
With backgrounds and skills in data science, applied research and heavy-duty coding, applied scientists are supposed to run the operations of a machine learning project. They are also responsible for managing the infrastructure and data pipelines needed to bring code to production.
4. Machine Learning Manager
One of the machine learning jobs is that of a Machine Learning Manager. As a machine learning manager, you need to have command of both the technical aspects of your job as well as the managerial aspect. You are expected to lead a team of machine learning engineers. You also need to guide your team through exploratory research projects. In addition, you are also responsible for management of the design, development, and evaluation of scalable models and algorithms. Scalable means having a learning algorithm which can deal with any amount of data, without consuming ever-growing amounts of resources like memory.
As a machine learning manager, you would be required to manage a lot of data, analyse big data using statistics and mathematics, track business outcomes to measure ROI, keep up with cutting-edge tools and techniques in your field of work, lead your team so they can efficiently carry out planning and execution, and manage your resources effectively.
Most organizations demand 10+ years of experience for this post. Your technical qualification should include working experience with either C/C++, Java, Python, Scala or R.
5. Software Engineer – Machine Learning
Several companies aim to hire software engineers with practical or educational exposure to machine learning. Knowledge of Java, C/C++, R or Python is generally a prerequisite. As a software engineer, your problem-solving skills will be tested. Along with your software skills, you must also be comfortable using machine learning algorithms to fit into this job profile. The job description for this profile includes designing, developing and debugging software programs for databases, applications, tools, and networks.
6. Machine Learning Forensic Analyst
Machine learning forensics is a newer application of machine learning. It aims to apply learning algorithms to detect and/or predict criminal activities and intent by studying previous crimes. It can be enlisted to detect network intrusions. In addition, it is used to discover evidence in corporate investigations.
This role will demand that you perform research on trained deep neural networks. This is so you can determine its behavior as a whole – ensemble layers and nodes and individual layers and nodes. Improving the accuracy of the classification models, by studying the false positives and false negatives, will also be a part of your job. The applicant needs to demonstrate fluency in deep learning systems and architectures. This also includes the tools used in deep learning systems.
While these are the prominent jobs, the good news is that these are not the only jobs. As you work in this field and gain experience, you’ll discover more roles. Something else might interest you better. You can make the switch then!
Since you are here, take a look at Have You Studied Machine Learning? Here Are 5 Industries You Can Work In!
