Can you explain a time when you applied machine learning or artificial intelligence to an automation problem?

Sample answer to the question

Oh, absolutely. So there was this one time when we had to streamline the ticket assignment process in our customer service software. We used a machine learning model to automatically classify and route tickets to the right team. I remember I was coding in Python, and we trained it on past tickets using a supervised learning approach. We chose an ensemble method that combined decision trees because they provided good accuracy without being too overfit. I also remember spending a bunch of time tweaking the feature extraction part to improve accuracy, and in the end, the system significantly reduced the time needed to route tickets!

A more solid answer

Absolutely! Let me give you a recent example: at my last job, we were facing a problem with the efficiency of our quality control in manufacturing. I spearheaded a project to integrate an AI system that could predict machine failures and streamline our maintenance schedules. My role involved coding a predictive model in Python, selecting features that were indicators of potential breakdowns. I engaged with a cross-functional team, including systems engineers and data analysts, creating alignment and ensuring that the system we were building fit seamlessly with our existing PLC/SCADA systems. The model used a combination of decision trees and neural networks to predict failures with over 90% accuracy. This allowed us to preemptively address issues, significantly reducing downtime by 30% and improving overall process quality.

Why this is a more solid answer:

This solid answer is an improvement because it demonstrates a clear understanding of the job role and the use of machine learning in a practical automation scenario. It reflects leadership and collaboration in a cross-functional team context related to the job description. Moreover, the candidate discusses software development and system integration skills through specific work with Python and PLC/SCADA systems, aligning with the qualifications listed. The answer also shows a connection to key responsibilities such as improving efficiency, process quality, and providing technical guidance. What could still be improved is a deeper analysis of the problem-solving process and a more vivid reflection of creativity and innovative thinking in developing the solution.

An exceptional answer

Yes, I had a fascinating challenge while working at my previous job. We needed to enhance our production line's efficiency by reducing manual intervention. Drawing on my expertise in automation technologies and machine learning, I initiated a project to incorporate an AI-driven robotics system that could adapt to different assembly tasks in real-time. My responsibility involved overseeing the software development for the AI algorithms and ensuring seamless integration with our existing PLC/SCADA systems. Collaborating with a team of software developers, systems engineers, and quality analysts, we used an innovative approach by combining convolutional neural networks for image recognition with reinforcement learning for decision-making. The AI was trained on a dataset of 100,000 assembly scenarios, which I carefully curated. Our success was marked by a 40% increase in automation level, a substantial decrease in human error, and a 25% improvement in production speed. Furthermore, my leadership within the project helped foster a culture of continuous innovation among my team, a key asset in maintaining our competitive edge in the industry. As an added bonus, we presented our findings at an international automation conference, demonstrating advanced problem-solving and strong communication skills.

Why this is an exceptional answer:

This exceptional answer hits all the key points by showcasing the candidate's direct involvement and leadership in a complex automation project that incorporates machine learning. The example demonstrates a deep level of expertise in both automation and machine learning, proficiency in software development, and a strong understanding of system integration—aligning perfectly with the job qualifications. It goes further by illustrating the analytical process involved in curating the training dataset and solving a real-world efficiency problem. The candidate also displays creativity in devising a unique solution, and clearly communicates the impact of the project on efficiency, production quality, and team innovation. This response also shows the candidate has experience with preparing and presenting technical reports, which is one of the responsibilities of the role.

How to prepare for this question

Research and prepare specific examples of when you applied machine learning or AI to an automation problem, aligning them with the job description.
Review your past projects and identify how you demonstrated expertise in automation technologies and system integration. Communicate these clearly.
Reflect on instances where you led a team or project, showcasing your ability to mentor, guide, and innovate alongside your colleagues.
Be specific about the technologies, algorithms, and programming languages you used, and how they contributed to solving the problem.
Consider discussing a project where your solution adhered to industry-specific regulations and cite this compliance in your answer to manifest your understanding of standards.
When preparing your answer, quantify the impact where possible (e.g., improved efficiency by 30%) to provide concrete evidence of the benefits of your work.
Think about your problem-solving process and be prepared to describe how you analyzed the problem, devised a strategy, and implemented it successfully.
Practice discussing complex technical topics in a clear and accessible way, demonstrating your communication skills, especially for instances where you might present these projects to an audience.

What interviewers are evaluating

Expertise in automation technologies
Proficient in software development and system integration
Strong analytical and problem-solving capabilities
Experience with PLC/SCADA systems
Understanding of machine learning and artificial intelligence as it applies to automation