Introduction
Do you want to make robots? It could just be feasible…
Artificial intelligence is becoming increasingly prominent in everyday life, therefore it’s no wonder that career opportunities in this field are growing. Furthermore, they may not only be easier to enter than you believe, but they may also be highly valuable. All you need to know is where to begin. We have collated the top 5 AI, ML, and Robotics positions to give you some idea about what to aim for. Here’s a brief description of each of them:
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Data Scientist
Data Scientist work starts with gathering data from various sources and analyses it to better understand how the business operates and develop AI solutions on specific use cases inside the organization.
Generates client insights, data scientists use machine learning algorithms to take the lead on a variety of AI-driven products and solutions.
They can assist clients in understanding how AI, data science, and machine learning may better their organization process — and provide a solution that serves them best — by leveraging their expertise in development, programming, and statistical analysis.
Because data science is multidisciplinary, iterative workflow is confusing, results are often difficult to interpret and explain, jargon is abundant, math is difficult for those unfamiliar with it, some models are black boxes, and there is hype around what can and cannot be done, data science work presents its own set of unique challenges.
What you’ll require: In addition to substantial expertise with data science and related tools (e.g., Python, R, SQL), you’ll need a bachelor’s degree (and, in certain cases, a master’s degree) in a related discipline. Attention to detail and problem-solving abilities and excellent organizational and communication skills are all essential.
Big Data Engineer
Big Data Engineers design, implement and optimize data products, architectures, and data sets, that break down the vast amounts of data into an easily accessible manner.
They ensure that downstream consumers have faster and easier access to the data. Big data engineers are responsible for ensuring that the company’s data pipelines are scalable, safe, and capable of handling numerous user requests.
Their work is critical in ensuring that an organization’s infrastructure is fully operational and secure, allowing Data Scientists to effectively acquire and analyze data.
They’re in charge of selecting and installing big data solutions and evaluating their efficacy and making recommendations for improvements, as needed and requested, read, extract, transform, stage, and load data into certain tools and frameworks.
What you’ll require: A degree is normally required, experience with Big Data technologies and workflow management tools and creating stream-processing systems. You’ll also require excellent project management, teamwork, and analytical abilities, as well as experience with object function scripting languages (e.g., Python, Java, Hadoop, Spark)
Machine Learning Engineer
Software engineers specializing in building artificially intelligent computers are known as Machine Learning Engineers.
The applications they work on may differ, but the overall objective is always the same: to create a machine that can learn from the past data, think, and act without being informed what to do.
At the nexus of software engineering and data science, machine learning engineers work. They use big data tools and programming frameworks to make sure that raw data from data pipelines is transformed into data science models that can be scaled as needed.
They’re also in charge of making the machine learning models to work in the real world, helping to scale theoretical data science models to production-level models that can manage terabytes of real-time data.
What you’ll require: A bachelor’s or Master’s in computer science is required, as well as considerable expertise in the industry. You’ll also need to be familiar with the most common computer programming languages. Statistical, analytical, and problem-solving talents are also necessary for a Machine Learning Engineer.
Software Engineer
While Software Engineers are needed in a variety of businesses, artificial intelligence and robots are growing increasingly in demand.
They design, create, test, and manage software systems for artificial intelligence programs or applications using a variety of programming languages. Software engineers must also collaborate with other IT professionals to guarantee that systems meet specific requirements.
As this sector is always growing, software engineers also undergo ongoing training and development to keep up with the newest programming languages and technologies.
Software engineers, on the other hand, don’t only write code; they also design everything from the ground up.
Software developers benefit from being detail-oriented since code is incredibly specific. Strong analytical abilities, problem-solving abilities, and a comfort level with complex concepts are also necessary. Creativity aids in the development of new software applications, while time management skills keep things on track. Employers prefer software engineers that are competent since timelines are critical to completing projects.
Software engineers are categorized into systems software developers and application software developers.
Software developers may be required to work for extended hours at times.
What you’ll require: Employers often look for demonstrated technical abilities, a bachelor’s degree in computer science, and proof of ongoing professional development by doing some certifications. You’ll also require problem-solving skills and analytical thinking, as well as excellent communication skills.
Automation Engineer
Automation Engineers design and implement automated test procedures for new or current artificial intelligence products using automation scripts and frameworks.
Their work is an important element of the software development process since it guarantees that the final product fulfills the purpose and meets business needs. It also indicates that any possible issues may be researched and addressed.
By gathering requirements and automating processes, automation Engineers have to collaborate closely with other teams to assist, find and remove difficulties. Sometimes they’ll be requested to automate service or business operations, and other times you’ll be requested to automate hardware or software.
Additionally, Automation Engineers communicate with developers frequently to ensure that the code they write aligns with established frameworks.
Test Automation Engineers are responsible for designing, developing, testing, and deploying successful software test automation systems.
Automation engineers employ suitable automation techniques to achieve the testing organization’s immediate and long-term goals with accuracy to perform this function.
What you’ll require: Programming language knowledge is required (e.g. Java, Python, etc.,), as is a high level of precision and attention to detail in all that you do. You won’t always need a degree to get started if you can demonstrate coding skills or relevant experience.
Conclusion
We have covered each of these top positions briefly. We hope that this helped you to understand what the top roles are in these fields and what you could be on the lookout for. Check out Great Learning Academy to understand more about these popular career paths and dive deeper. Hope it helps you upskill and power ahead!
