The Evolvers Group is a pioneering tech company at the forefront of innovation and development in the machine learning space. Renowned for its forward-thinking approach, The Evolvers Group has established itself as a leader by providing cutting-edge solutions to complex problems through machine learning and AI technologies.

Stepping into the role of a Machine Learning Engineer at The Evolvers Group involves tackling high-impact projects that require robust technical expertise in areas such as algorithm development, data analysis, and model optimization. As part of the team, you will innovate and optimize systems to drive significant advancements in various domains.

If you're considering elevating your career with a firm that values both innovation and intellectual growth, this guide is for you. In this guide, Interview Query takes you through the interview process, including typical questions and essential tips for success. Let’s get started!

Submitting Your Application

The first step is to submit a compelling application that reflects your technical skills and interest in joining The Evolvers Group as a Machine Learning Engineer. Whether you were contacted by a recruiter from The Evolvers Group 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 Evolvers Group 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 Evolvers Group's 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 Machine Learning Engineer role at The Evolvers Group is usually conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around machine learning algorithms, data preprocessing techniques, and Python programming.

In the case of senior roles, take-home assignments regarding model implementation, optimization problems, and data analysis are incorporated. Apart from these, your proficiency against statistical methods, deep learning frameworks, and data science fundamentals 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 Evolvers Group office. Your technical prowess, including machine learning modeling capabilities and coding skills, 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 The Evolvers Group.

Quick Tips For The Evolvers Group Machine Learning Engineer Interviews

• Understand the Basics: Brush up on your Python coding skills and fundamental machine learning algorithms, as you will be tested on your basics.
• Know Your Projects: Be prepared to discuss your previous work experience and projects in detail. The interviewers may ask about challenges faced, solutions implemented, and the impact of your work.
• Be Analytical: Demonstrate your problem-solving and analytical thinking skills. Be prepared for case studies or real-scenario problem assignments that test how you approach complex issues.

Typically, interviews at The Evolvers Group 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 find the maximum number in a list of integers. Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

• Create a function convert_to_bst to convert a sorted list into a balanced binary tree. Given a sorted list, create a function convert_to_bst that converts the list into a balanced binary tree. The output binary tree should have a height difference of at most one between the left and right subtrees of all nodes.

• Write a function to simulate drawing balls from a jar. Write a function to simulate drawing balls from a jar. The colors of the balls are stored in a list named jar, with corresponding counts of the balls stored in a list called n_balls.

• Develop a function can_shift to check if one string can be shifted to become another. Given two strings A and B, write a function can_shift to return whether or not A can be shifted some number of places to get B.

• What are the drawbacks of having student test scores organized in the given layouts? Assume you have data on student test scores in two different layouts. Identify the drawbacks of these layouts and suggest formatting changes to make the data more useful for analysis. Additionally, describe common problems seen in "messy" datasets.

• How would you locate a mouse in a 4x4 grid using the fewest scans? You have a 4x4 grid with a mouse trapped in one of the cells. You can scan subsets of cells to know if the mouse is within that subset. Describe a strategy to find the mouse using the fewest number of scans.

• How would you select Dashers for Doordash deliveries in NYC and Charlotte? Doordash is launching delivery services in New York City and Charlotte. Describe the process for selecting Dashers (delivery drivers) and discuss whether the criteria for selection should be the same for both cities.

• What factors could bias Jetco's study on boarding times? Jetco, a new airline, has the fastest average boarding times according to a study. Identify potential factors that could have biased this result and explain what you would investigate further.

• How would you design an A/B test to evaluate a pricing increase for a B2B SAAS company? You work at a B2B SAAS company interested in testing different subscription pricing levels. Describe how you would design a two-week-long A/B test to evaluate a pricing increase and determine if it is a good business decision.

• How much should we budget for a $5 coupon initiative in a ride-sharing app? A ride-sharing app has a probability (p) of dispensing a $5 coupon to a rider and services (N) riders. Calculate the total budget needed for the coupon initiative.

• What is the probability of both or only one rider getting a coupon? A driver using the app picks up two passengers. Determine the probability of both riders getting the coupon and the probability that only one of them will get the coupon.

• What is a confidence interval for a statistic and why is it useful? Explain what a confidence interval is, why it is useful to know the confidence interval for a statistic, and how to calculate it.

• What is the probability that item X would be found on Amazon's website? Amazon has a warehouse system where items are located at different distribution centers. Given the probabilities that item X is available at warehouse A (0.6) and warehouse B (0.8), calculate the probability that item X would be found on Amazon's website.

• Is a coin that comes up tails 8 times out of 10 fair? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if this is a fair coin.

• What are time series models and why are they needed? Describe what time series models are and explain why they are necessary when less complicated regression models are available.

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

• How would you evaluate the suitability and performance of 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 and assess its performance before and after deployment?

• How does random forest generate the forest, and why use it over logistic regression? Explain the process by which random forest generates its forest. Additionally, discuss why one might choose random forest over other algorithms like logistic regression.

• How would you explain linear regression to a child, a first-year college student, and a seasoned mathematician? Explain the concept of linear regression tailored to three different audiences: a child, a first-year college student, and a seasoned mathematician.

• What are the key differences between classification models and regression models? Describe the main differences between classification models and regression models.

Considering The Evolvers Group for the Machine Learning Engineer position based on various interview experiences and job postings is a promising career move. If you want more insights about the company, check out our main The Evolvers Group Interview Guide, where we have 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 The Evolvers Group’s 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 The Evolvers Group machine learning engineer interview questions and challenges.

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!