Clarifai is a pioneering deep learning AI platform that excels in computer vision, natural language processing, LLMs, and audio recognition. Since its inception in 2013, Clarifai has transformed unstructured data into actionable insights at unprecedented speeds and accuracies. Headquartered in the U.S., the company has a global remote presence with employees in Canada, Argentina, India, and Estonia.

As a Software Engineer at Clarifai, you'll be pivotal in developing and optimizing ML infrastructure. Your role will involve working closely with research teams, innovating new training frameworks, and ensuring scalable, high-performance solutions. The position demands 5-8+ years of experience in machine learning systems and familiarity with tools like TensorFlow and PyTorch. Competitive salaries range from $150,000 to $200,000, depending on relevant experience.

In this guide, we'll walk you through the interview process for Clarifai's Software Engineer role, common interview questions, and tips to excel. 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 Clarifai as a Software Engineer. Whether you were contacted by a Clarifai 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 Clarifai 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 Clarifai Software 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 Clarifai Software Engineer role usually is conducted through virtual means, including video conference and screen sharing. Questions in this 1-hour long interview stage may revolve around Clarifai’s machine learning systems, ETL pipelines, and algorithm design.

Technical exercises, including coding challenges and system design questions, may also be assessed during this round. Your proficiency in programming languages like Python and frameworks like TensorFlow or PyTorch will likely be put to the test.

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, which can also be remote given the current working conditions at Clarifai. Your technical prowess, including ML modeling capabilities, programming, and system design, 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 Software Engineer role at Clarifai.

Quick Tips For Clarifai Software Engineer Interviews

A few tips for acing your Clarifai interview include:

• Deep Dive into AI/ML Concepts: Clarifai is a leader in AI and ML technologies. Brush up on your knowledge of machine learning frameworks, deep learning models, and the latest trends in AI research.
• Problem-Solving Skills: Be prepared to solve complex algorithm problems. Practice a variety of coding questions and system design scenarios using Interview Query.
• Understand Clarifai's Products: Familiarize yourself with Clarifai’s suite of AI products and services. Think about how you can contribute to their existing technology stack and possibly bring innovative solutions to their processes.

Typically, interviews at Clarifai vary by role and team, but commonly Software 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.

• Write 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.

• Write 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. Write a function to search for a target value in the array and return its index, or -1 if not found. 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 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.

• Write a function to calculate sample variance. Create 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 suspicious about the A/B test results? Your manager ran an A/B test with 20 different variants and found one significant result. Evaluate if there is anything suspicious about these results.

• How to 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. Example datasets: Messy Dataset

• How would you evaluate whether using a decision tree algorithm is the correct model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will pay back a personal loan. How would you evaluate if a decision tree is the right choice, and how would you assess its performance before and after deployment?

• How does random forest generate the forest and why use it over logistic regression? Explain the process of how a random forest generates its forest. Additionally, discuss why one might choose random forest over logistic regression for certain problems.

• When would you use a bagging algorithm versus a boosting algorithm? Compare two machine learning algorithms. Describe scenarios where you would prefer a bagging algorithm over a boosting algorithm and discuss the tradeoffs between the two.

• How would you justify using a neural network model and explain its 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?

• 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 completed a V1 of the model. What metrics would you use to track the model's accuracy and validity?

What is the average salary for a Software Engineer at Clarifai?

Q: What does Clarifai do?
Clarifai is a leading AI platform that focuses on deep learning for computer vision, natural language processing, large language models (LLMs), and audio recognition. We transform unstructured data like images, videos, text, and audio into structured data much faster and more accurately than humans.

Q: What would be my impact as a Software Engineer at Clarifai?
You would play a crucial role in contributing to our core machine learning (ML) infrastructure. Your work will help researchers and users train and deploy state-of-the-art models for our customers.

Q: What opportunities do Software Engineers have at Clarifai?
You will have the opportunity to: - Collaborate with research teams to design and build our training infrastructure. - Prototype new training frameworks and productionize solutions at scale. - Design, optimize, and test model integration infrastructure. - Work with the data team to implement ETL/ELT pipelines.

Q: What are the requirements for a Software Engineer position at Clarifai?
- 5-8+ years of experience in developing machine learning infrastructure. - Familiarity with setting up ML lifecycle systems. - Comfortable working with open-source software. - Hands-on experience in implementing production machine learning systems at scale.

Q: What’s the salary range for this position?
The hiring salary range for this position is between $150,000 and $200,000, flexible depending on relevant experience.

If you are excited about contributing to cutting-edge AI technology and want to make a significant impact, Clarifai offers an incredible opportunity to be at the forefront of machine learning innovation. Our Software Engineer position provides the platform to collaborate with top-tier research teams, prototype and scale groundbreaking training frameworks, and work with a diverse range of technologies. To better prepare yourself for this unique opportunity, explore our detailed interview guidelines on Interview Query where we cover potential interview questions and offer insights on the interview process. Additionally, our extensive company interview guides can equip you with the essential tools needed for success. Good luck with your interview!