Bentley Systems (Nasdaq: BSY) is a global leader in providing innovative software solutions that advance infrastructure engineering, supporting the global economy and environment. Our industry-leading applications are pivotal for professionals in the design, construction, and operations of roads, bridges, rail, water systems, and more, generating over $1 billion in annual revenues across 194 countries.

If you aspire to join Bentley as a Senior Machine Learning Engineer, you will be instrumental in developing and deploying advanced image detection and geospatial models. Your role involves collaboration, rapid development, and leveraging the latest machine learning frameworks to drive the company's growth. This guide by Interview Query will navigate you through Bentley's interview process and core expectations for this role.

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining Bentley Systems as a Machine Learning Engineer. Whether you were contacted by a Bentley recruiter or have taken the initiative yourself, carefully review the job description and tailor your CV according to the prerequisites.

Tailoring your CV may include identifying specific keywords that the hiring manager might use to filter resumes and crafting a targeted cover letter. Furthermore, don’t forget to highlight relevant skills and mention your work experiences.

Recruiter/Hiring Manager Call Screening

If your CV happens to be among the shortlisted few, a recruiter from the Bentley Talent Acquisition Team will make contact and verify key details like your experiences and skill level. Behavioral questions may also be a part of the screening process.

In some cases, the Bentley Machine Learning Engineer hiring manager stays present during the screening round to answer your queries about the role and the company itself. They may also indulge in surface-level technical and behavioral discussions.

The whole recruiter call should take about 30 minutes.

Technical Virtual Interview

Successfully navigating the recruiter round will present you with an invitation for the technical screening round. Technical screening for the Bentley Machine Learning Engineer role usually is conducted through virtual means, including video conferences and screen sharing. Questions in this 1-hour long interview stage may revolve around Bentley’s data systems, ETL pipelines, and machine learning models.

In addition, practical coding tests or take-home assignments regarding machine learning pipelines and computer vision might be included. Your proficiency with image processing libraries such as OpenCV, neural networks, and machine learning frameworks like TensorFlow or PyTorch may also be assessed during the round.

Depending on the seniority of the position, case studies and similar real-scenario problems may also be assigned.

Onsite Interview Rounds

Followed by a second recruiter call outlining the next stage, you’ll be invited to attend the onsite interview loop. Multiple interview rounds, varying with the role, will be conducted during your day at the Bentley office. Your technical prowess, including programming and ML modeling capabilities, will be evaluated against the finalized candidates throughout these interviews.

If you were assigned take-home exercises, a presentation round may also await you during the onsite interview for the Machine Learning Engineer role at Bentley.

Quick Tips For Bentley Systems Machine Learning Engineer Interviews

You should plan to brush up on any technical skills and try as many practice interview questions and mock interviews as possible. A few tips for acing your Bentley Systems Machine Learning Engineer interview include:

• Showcase Your Technical Proficiency: Bentley places a high value on technical skills, particularly in machine learning frameworks like TensorFlow, PyTorch, and experience with NVIDIA.
• Be Innovative: Bentley values creativity and innovation. Be prepared to propose creative solutions and demonstrate your ability to develop new tools and products.
• Understand Bentley’s Core Values: Embody the spirit of Bentley’s collaborative and ambitious culture. Practice responding to behavioral questions that highlight your ability to work with a team and drive rapid development.

Typically, interviews at Bentley Systems vary by role and team, but commonly Machine Learning Engineer interviews follow a fairly standardized process across these question topics.

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: Determine the time complexity.

• Create a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of (O(n)) required.

• Develop a function precision_recall to calculate precision and recall metrics from a 2-D matrix. Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

• Write a function to search for a target value in a rotated sorted array. Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand. You are given a target value to search. If the value is in the array, return its index; otherwise, return -1. Bonus: Your algorithm's runtime complexity should be in the order of (O(\log n)).

• Would you think there was anything fishy about the results of an A/B test with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect any issues with the results?

• How would you set up an A/B test to optimize button color and position for higher click-through rates? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• What would you do if friend requests on Facebook are down 10%? A product manager at Facebook reports a 10% decrease in friend requests. What steps would you take to address this issue?

• Why might the number of job applicants be decreasing while job postings remain constant? You observe that the number of job postings per day has remained stable, but the number of applicants has been steadily decreasing. What could be causing this trend?

• What are the drawbacks of the given student test score datasets, and how would you reformat them for better analysis? You have data on student test scores in two different layouts. What are the drawbacks of these formats, and what changes would you make to improve their usefulness for analysis? Additionally, describe common problems in "messy" datasets.

• Is this a fair coin? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

• How do you write a function to calculate sample variance? Write a function that outputs the sample variance given a list of integers. Round the result to 2 decimal places. Example input: test_list = [6, 7, 3, 9, 10, 15]. Example output: get_variance(test_list) -> 13.89.

• Is there anything fishy about the A/B test results? Your manager ran an A/B test with 20 different variants and found one significant result. Would you suspect anything unusual about these results?

• How do you find the median in (O(1)) time and space? Given a list of sorted integers where more than 50% of the list is the same repeating integer, write a function to return the median value in (O(1)) computational time and space. Example input: li = [1,2,2]. Example output: median(li) -> 2.

• What are the drawbacks of the given data organization? You have data on student test scores in two different layouts. Identify the drawbacks of these layouts, suggest formatting changes for better analysis, and describe common problems in "messy" datasets.

• How would you evaluate and deploy a decision tree model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will repay a personal loan. How would you evaluate whether a decision tree is the correct model? If you proceed, how would you evaluate the model's performance before and after deployment?

• How does random forest generate the forest and why use it over logistic regression? Explain how random forest generates its forest of trees. Additionally, why would you choose random forest over other algorithms like logistic regression?

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. In which scenarios would you use a bagging algorithm versus a boosting algorithm? Provide examples of the tradeoffs between the two.

• How would you justify using a neural network to solve a business problem? Your manager asks you to build a model with a neural network to solve a business problem. How would you justify the complexity of building such a model and explain the predictions to non-technical stakeholders?

• What metrics would you use to track the accuracy and validity of a spam classifier? You are tasked with building a spam classifier for emails and have built a V1 of the model. What metrics would you use to track the accuracy and validity of the model?

What is the average salary for a Machine Learning Engineer at Bentley Systems?

Q: What are the primary responsibilities for the Senior Machine Learning Engineer position at Bentley Systems?

The role focuses on developing and enhancing our pipeline to process georeferenced images. Key tasks include building tools for image detection and segmentation models, automating internal processes, researching new technologies, augmenting neural networks for specific applications, and collaborating with the engineering team to propose innovative solutions.

Q: What skills are desired for a Senior Machine Learning Engineer at Bentley Systems?

Candidates should have a background in computer science, engineering, or a related field, along with hands-on experience in building data and machine learning pipelines. Proficiency in Python, experience with NVIDIA, and familiarity with frameworks such as PyTorch, TensorFlow, MxNet, and Keras are required. Additionally, knowledge of image processing libraries like OpenCV and computer vision experience are important.

Q: What is Bentley Systems' work environment like?

Bentley Systems offers a hybrid work model, with two days in the office and three days remote. The team is close-knit and thrives on rapid development and innovation in big-data geospatial systems.

Q: What educational qualifications are preferred for this role?

While a Bachelor's degree in computer science, engineering, or a related field is desired, candidates with equivalent experience are also encouraged to apply. Advanced degrees like a Master's or PhD in Computer Science, Physics, Engineering, or Math are highly valued.

Q: How can I prepare for an interview with Bentley Systems?

Preparation should include familiarizing yourself with the company's innovative software solutions and infrastructure projects. Utilize resources like Interview Query to practice relevant interview questions and enhance your technical skills.

Get ready to embark on an exhilarating journey with Bentley Systems as a Senior Machine Learning & Computer Vision Engineer! This role offers an exceptional opportunity to work on advanced geospatial systems and collaborate with a cutting-edge team focused on rapid development and innovative solutions. If you're passionate about automating processes and advancing machine learning pipelines, this is the perfect environment for you to thrive and make a substantial impact.

For more insights about Bentley Systems, check out our main Bentley Systems Interview Guide where we've covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Bentley Systems' interview process for different positions.

At Interview Query, we empower you to unlock your interview prowess with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every Bentley Systems machine learning engineer interview question and challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!