What Do Machine Learning Engineers Actually Do?

June 21, 2021

Using AI reasoning and uncertainty to set and achieve complex objectives.
Applying machine-learning concepts, logic, and probability analysis to solve complex problems.
Analyzing AI and machine learning-based systems to monitor and control project development.
Using AI and machine learning best practices for processes like speech recognition, data processing, data mining, and robotic control.

Machine learning uses classical algorithms to complete complex tasks, like clustering, regression, or classification projects, and the algorithms driven by machine learning processes must be trained on data before they’re able to operate effectively. The more the algorithms are trained, the better they’re able to complete the tasks they’ve been assigned.
AI is a term that’s used broadly and applies to any applications where a machine attempts to mimic human cognitive functions, like learning or problem-solving. AI systems can get incredibly complex, but they can also be as simple as a series of nested if-else statements.

Entertainment – Machine learning technology is being used to review user behavior, predict demand, then customize suggestions for movies, music, TV shows, advertisements, and more.
Healthcare – Machine learning and AI solutions are being used to power autonomous surgical robots, virtual nursing assistants, automated image diagnosis, and reduce dosage errors.
Manufacturing – Machine learning and AI-driven robots have been used for years to increase profit margins by improving efficiency and accuracy, reducing waste, down-time, and cost overruns.
Sports – Machine learning automation and predictive analyses are being used to help determine important business decisions around sponsorship activations, ticket sales, and even athletic performance.
Transportation – Machine learning and AI technology have been integrated into self-driving cars, and widescale testing is now underway to literally remove the human component from the act of driving, providing truly autonomous vehicles.

Understanding, analyzing, and applying AI and machine learning principles for reasoning processes and uncertainty.
Utilizing machine learning and techniques to perform image analysis and reconstruction, along with other similar tasks.
Solving a variety of complicated problems and scenarios by implementing machine learning and AI-driven solutions.
Designing, then building machine learning and AI-based solutions to perform complex tasks, modeling, or improving upon typical human behavior.
Devising and building effective solutions that integrate both machine learning principles and AI best practices to solve complex problems.
Evaluating and improving applications that rely on machine learning and AI processes.

Deep-learning libraries, such as Tensorflow.
Experience using machine learning solutions to solve complex problems in healthcare, manufacturing, oil/gas, and automotive.
Proficiency in Python programming.

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What Do Machine Learning Engineers Do?