Machine learning (ML) has been under the spotlight in recent years in the tech world. It has applications in nearly all fields. Moreover, as it has a diverse range of applications, machine learning jobs have sprouted up in numerous industries. So, with more companies utilizing the machine learning model, there is a growing demand for MI professionals.
Here is a list of the top 6 machine learning jobs worth pursuing in 2022.
1. Data Scientist
Data scientists add value to an organization by collecting, processing, and analyzing data. Nearly every organization has to handle vast volumes of data consistently. Likewise, it would not be humanly possible to collate and analyze such volumes without the help of technology. That’s why companies employ machine learning modeling techniques for making accurate predictions that can drive business models.
Data scientists must have specialization in at least one programming language, such as R or Python. They must also be adept at
- Extracting and manipulating data with SQL.
- Building machine learning algorithms.
- Analyzing datasets using statistical techniques.
2. MLOps Engineer
MLOps engineers must convert data science code into a functional end product. They also must create business models and incorporate them into the company’s website. Additionally, they must develop systems that direct potential customers to pages that serve their requirements. MLOps engineers must also check various metrics and logs to ensure the business is on the right track. They must implement multiple access control mechanisms, also verify that the infrastructure is in line with the compliance policies.
MLOPs engineers must work with machine learning libraries like PyTorch and TensorFlow. Having these skills in the toolbelt is a definite advantage. They must also have a good idea about the fundamentals of ML algorithms. They must be skilled in
- Refactoring data scientists’ codes and keeping them production ready.
- Have a good understanding of software development and MLOps concepts such as CI/CD pipelines.
3. Machine Learning Engineer
The job of a machine learning engineer is to design scalable AI products for end users. Machine learning engineers must also build machine learning pipelines and train employees. They must also constantly monitor model performance and reeducate the handlers when needed. In this competitive field, having a well-crafted machine learning engineer resume becomes paramount to distinguish oneself from other jobseekers and demonstrate the expertise and experience necessary to excel in this demanding role.
Machine learning engineers are placed somewhere between data science and software engineering. But, they must understand the working of both domains. Machine learning engineers must:
- Learn statistics, probability, and the fundamentals of ML modeling.
- They must understand software engineering principles like abstraction, modularity, and version control.
- Have knowledge of MLOps.
- Must be aware of the best practices associated with incorporating data science models into production.
4. Data Science Consultant
Data science consultants offer machine learning and AI solutions for their clients. Additionally, most consultants work on multiple projects with clients in different industries. Machine learning strategy consultants offer AI-driven strategies to solve problems, but they do not implement them.
Data science consultants offer and implement fully functional ML products for their clients.
- Data science consultants must know the building process of machine learning algorithms. They must analyze vast amounts of data and offer valuable solutions.
- They must know how to translate data into actionable insights that non-technical people can understand.
5. Machine Learning Research Scientist
A machine learning scientist generally finds opportunities in academic settings where ML research is a top priority. A high level of accuracy is expected of ML research scientists. They also manage end-to-end project workflows.
Most researchers specialize in a single ML field area and continue exploring new opportunities in that specific niche.
- Machine learning researchers must have skills in writing research papers.
- They must have a good grasp of at least one programming language.
- ML skills in a specific field (Optimization/ Regression analysis) can be an added advantage.
6. Computer Vision Engineer
Computer vision engineers develop object detection, face recognition, and pose estimation models for various organizations. So, the computer vision engineer’s job is highly specialized, as their focus is limited to a distinct domain.
Computer Vision Engineers must come up with innovative solutions or make improvements to existing ones.
- Engineers must have strong programming skills and software engineering principles.
- They must be experts at solving DSA or Data Structures and Algorithms
- They must have good calculus, statistics, mathematical optimization, and linear algebra knowledge.
Machine learning skills can result in fulfilling careers. Likewise, the opportunities are endless if you have skills in a specific area like speech recognition or computer vision. Also, all machine learning roles come with attractive salaries. They also offer room for continuous progress and improvement. So, you must look for ML job opportunities that match your decision interests and capabilities.