The Google UX Researcher role is an exciting opportunity to be part of a dynamic and collaborative team at Google that includes UX Designers, Writers, Content Strategists, Program Managers, and Engineers. Together, the team gathers deep insights into the behaviors, wants, and emotions of its users—which serves as a foundation to inspire and inform Google's UX design decisions. Review the Facebook UX Researcher and Amazon UX Researcher guides for related insights.

As a User Experience Researcher (UXR), your role is crucial in helping your team truly understand user behaviors, needs, and motivations. You'll engage in primary research activities that may include field studies, 1:1 interviews, workshops, surveys, testing, logs analysis, and so on. 

The average yearly total compensation for this role is $244,000, comprising a base salary of $153,000, stock options worth $60,000 per year, and an annual bonus of $31,000.

The Google UX Researcher interview process typically consists of three main rounds:

Your Competitive Edge: Google's UX Researcher Interview Handbook - Transform Yourself into the Ideal Candidate

Engineering Managers at Google are responsible for leading a team of software engineers in the development and delivery of high-quality products and services. For insights into similar roles, see the Microsoft Engineering Manager guide. They also hire, mentor, and develop high-performing engineers, create and maintain a positive and productive work environment, and represent the team to senior management and other teams within Google.

Google EMs play a critical role in the success of Google's products and services. They are responsible for ensuring that Google's products are developed and delivered on time, within budget, and to the highest quality standards. They also play a key role in attracting and retaining top talent, and in creating a positive and productive work environment. 

How to Apply for an Engineering Manager Job at Google?

Check the job openings on Google’s careers page or on LinkedIn. Apply for the one which feels relevant for your background. If you can get a referral - this meaningfully increases your chances of getting an interview call. Make sure it's a "relevant" referral though; in Google in particular if you're applying for an EM role - you ideally want another EM; or at the very least someone with an Engineering background to refer you; for the referral to be valued properly. Also please definitely make sure your resume has the basics sorted. Concise, impact focused overviews of your past roles - in particular those focusing on people leadership and craft excellence. Ideally past experience of Engineering Management (Google practically never hires people who have purely held IC roles in the past for an EM role). If you want specific targeted advice on whether your resume is making the cut; or whether it needs changes, Prepfully has several Google recruiters who actively hire EMs, and who can give you this sort of advice.

As a part of the Google EM interview, you’ll will need to go through multiple interview rounds:

1. Recruiter Screening - This round is taken by a recruiter for a basic background check. You can also expect typical behavioral and resume-related questions.

2. Technical Screening - This round includes data structures and algorithms related questions. You will be asked to present answers in the algorithm method and to optimize the code.

3. Onsite Interview - In this final round, you will typically face the following interviews: Leadership Interviews, System Design Interview and Coding/Code Review Interview (Google gives you a choice between Coding and Code Review).

A comprehensive guide of the Google engineering manager interview. Get details of job role, interview process and sample questions. 

Google engineering manager interview guide

Detailed, specific guidance on the Google Engineering Manager interview process - with a breakdown of different stages and interview questions asked at each stage of the Google EM loop, including Google-specific interview types such as the "Code review" round

Google Engineering Manager Interview Guide

Amazon is the world's largest e-commerce company and also a major technology firm. Whether it is its dynamic e-commerce platform, intelligent virtual assistant Alexa or the reliable cloud computing service AWS, Amazon has an ever-growing presence in the digital sphere and is constantly in need of data scientists who can stretch the growth horizons of the company through ingenious data-driven decisions. For more resources, see the Meta DS Analytical Reasoning and Doordash Data Scientist guides.

Median salary       :USD 300,000 with base component being USD 151,000, stock component being USD 128,000 and bonus being USD 21,000.

The role of a data scientist at Amazon is not fixed as such and depends on the specific team one is assigned to. Here are the different data science teams at Amazon:

Demand forecasting team in the Supply Chain Optimization Technologies (SCOT).

The NASCO Team (North America Supply Chain Organization).

Middle Mile Planning Research Optimization Science (mmPROS) team, and many more. 

Here are the roles and responsibilities in a little more detail:

Design, develop, evaluate, deploy and update data-driven models and analytical solutions for machine learning (ML) and natural language (NL) applications.

Develop cutting edge data pipelines, build accurate predictive models, and deploy automated software solutions to provide forecasting insights.

Research, design, and improve models with business impact in mind.

Demand Forecasting Team - Improve upon existing Demand Forecasting statistical or machine learning methodologies by developing new data sources, testing model enhancements, running computational experiments, and fine-tuning model parameters for new forecasting models.

SCOT Team - Analyse large amounts of data from different parts of the supply chain and their associated business functions. Improve upon existing machine learning methodologies by developing new data sources, developing and testing model enhancements.

AWS Team - Simplify and drive automation of the forecasting process by building new tools and onboarding existing ones from Amazon Retail or AWS. Support engineering teams to build tools and applications on Amazon's unique big data platform to efficiently generate and deploy insights into decision-making systems at AWS.

PhD in Artificial Intelligence, Computer Science, Statistics, Applied Math or a related field.

Previous experience in a ML, data scientist or optimization engineer role with a large technology company.

Experience in an operational environment developing, fast-prototyping, piloting and launching analytic products.

Ability to develop experimental and analytic plans for data modelling processes, use of strong baselines, ability to accurately determine cause and effect relations.

Experience in creating data-driven visualizations to describe an end-to-end system.

Experience in Statistical Software such as R, Weka, SAS, SPSS

Able to write SQL scripts for analysis and reporting (Redshift, SQL, MySQL).

Experience using one or more Python, R, Java, C++ VBA, MATLAB, programming languages.

Excellent written and verbal communication skills.

Much like other big tech companies, Amazon follows a 3 stage interview process for selecting candidates for its Data Scientist role. The process comprises an initial phone screen by a hiring manager, followed by a technical screen, and concludes with an onsite interview. The onsite round is a full-day event and consists of five 1:1 interviews with one of Amazon's Data Scientists and HR manager.

Detailed, specific guidance on the Amazon Data Scientist interview process - with a breakdown of different stages and interview questions asked at each stage

In a customer-centric company like Amazon, software engineers play a crucial role in building complex software systems and delivering them to the customer. They work closely with business, design, and development teams to collect requirements, assess risks, and work on customer impact. Explore related opportunities in the Netflix Software Engineer and Databricks Software Engineer guides.

Amazon Software Engineer interview is designed to test your ability of implementing software engineering strategies to communicate with the customers, collect requirements, design and deploy the products. For this, they are required to be proficient coders and have experience in working with software development methods like Agile and Scrum. 

Requirements for an Amazon Software Engineer -

Proficiency in programming languages like Java/C++ and experience with object-oriented programming.

Ability to deal with databases and design back-end systems, as well as integrate them with front-end and other frameworks. 

Knowledge of data structures and CS fundamentals. They must also possess design and architectural skills and be able to implement these designs.

These are important requisites to land the role of Amazon SDE interview. Let's look at some key pointers about the interview process for the Amazon software engineering role.

The Amazon Software Engineer interview consists of 6-7 interviews across 3 rounds.

The first round is an HR interview, which is a general discussion about the role and your experiences. The next round is the Technical Phone Screen, which tests your coding and problem-solving skills and focuses on data structures. The final round is the onsite round, which consists of 4-5 interviews, wherein, one round is a behavioural interview and the rest are technical interviews.

Impress your way in the Amazon SDE Interview! Our comprehensive Amazon software engineer interview guide covers everything you need to know to land the job. From common interview questions to insider tips and tricks, Prepfully has got you covered.

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Ace Your Amazon Software Engineer Interview (Amazon SDE Interview Prep)

Detailed, specific guidance on the Amazon Software Engineer interview process - with a breakdown of different stages and interview questions asked at each stage

A Technical Program Manager(TPM) at Google plays a critical role in helping drive company strategy, aligning teams, collaborating with cross-functional stakeholders, and delivering on multiple complex projects for the company. Given the rapid expansion of companies in the digital space, it has become imperative for companies, especially ones with a large digital footprint, to hire TPMs.

Google is a technology giant with products across the hardware and software domain. Google needs TPMs who can lead and manage technical projects and help achieve its product development and growth targets. Consider reviewing the Meta Technical Program Manager guides for a broader perspective.

Google TPMs put on different hats depending upon the teams/programs they are assigned to. Some of the different teams at Google where Technical Program Managers have to lend their services are:

Here's a generic description of the roles and responsibilities of a TPM at Google

Provide the required hands-on software development and project management, cross-functional coordination, and inter/intra team communications to deliver outstanding program outcomes.

Work closely with software engineers, QA, product managers and other engineering teams to get high-quality products and features through the software project lifecycle (build, test and release on time).

Manage project schedules, identify possible issues and clearly communicate them to project stakeholders.

Take responsibility for release schedules and milestones, keeping up a high velocity in a fast-paced environment.

 Lead several technical programs for the Google Cloud Business, setting priorities for products and engineering, leading cross-functional teams to take products to market, ensuring success metrics are informing future efforts, and quickly fine tuning the program as needed. Check out the Tesla Technical Program Manager and Stripe Technical Program Manager guides for additional insights.

Skills/Qualifications required for Google Technical Program Manager Role

Bachelor’s degree in a technical field or equivalent practical experience.

Experience in software program management and/or engineering management.

Experience in Software Engineering, Software Infrastructure Engineering, Security, Big Data and Analytics, or Cloud Networking.

Experience in problem solving within fast-paced and constantly changing environments.

Experience working cross-functionally in a highly integrated team composed of both technical and non-technical members.

Experience in communicating technical concepts to non-technical audiences.

Strong spoken and written communication skills.

Google Technical Program Manager(TPM) salary

Median salary      :USD 233,000 with base component being USD 143,000, stock component being USD 64,000 and bonus being USD 25,000.

The interview process for the Google Technical Program Manager role consists of 3 stages as under:

Here's a detailed look at the entire Google TPM interview process, starting with the initial screen

Practice questions and Mock Interview for Google Technical Program Manager. Get details of interview rounds, questions and other details on Google TPM role.

Google Technical Program Manager Interview Preparation

Detailed, specific guidance on the Google Technical Program Manager interview process - with a breakdown of different stages and interview questions asked at each stage

Google Technical Program Manager Interview

Program managers typically oversee a group of projects (and in some cases, a team of project managers), each of which is linked by a common aspect, such as a single company target. They are also in charge of strategy, ensuring that everything is moving in the right direction and on the right timelines. 

An efficient program manager will help create a more cohesive and successful team. Therefore when organizations are looking for applicants to lead various projects and teams, they go through a rigorous screening process to ensure the candidate has a positive effect on others as well as the company.

This guide will walk you through the Google Program Manager interview process, including useful tips and tricks to help you ace the interview. For similar roles, check out the Amazon Program Manager and Facebook Project Manager guides. Additionally, the Uber Program Manager Interview Guide offers insights into another key player in the tech industry.

Google's program manager interview process is lengthy and time-consuming. Itusually takes 3-8 weeks, although it is not unusual for it to take much longer. Here's a rundown of the interview stages you'll encounter:

Phone screen with a hiring manager and program managers

Detailed, specific guidance on the Google Program Manager interview process - with a breakdown of different stages and interview questions asked at each stage

Google engineers are at the forefront of developing groundbreaking technologies that reshape how users connect, explore, and interact with information and each other. As a result, Google actively seeks out adaptable and passionate engineers who can tackle new challenges and drive technology forward.

Being a part of an exceptionally creative, motivated, and skilled hardware engineering team, you'll have the opportunity to create new products that impact millions of people. For hardware roles at other top tech companies, explore the Apple Hardware Engineer and Google Thermal Engineer guides. In this role, you'll be instrumental in shaping charging experiences for Google hardware products, enhancing their performance and reliability. You'll collaborate closely with product management and cross-functional engineering teams to define solutions, implement hardware, and seamlessly integrate features with software and Android OS teams.

For hardware engineers, the average total compensation per year is $198,306, which includes:

Google Hardware Engineer - Interview Guide

The Google Hardware interview process comprises three key stages:

Technical phone screening with a Hiring Manager, and

The Ultimate Guide to Acing Google's Hardware Engineer Interviews: Insider Strategies, Tips, and Techniques for Your Career Success

The Amazon Bar Raiser interview is a crucial part of the company's hiring process, aimed at ensuring that the highest hiring standards are maintained. 

In this blog, we will delve into the intricacies of the Bar Raiser interview, understanding the role of a Bar Raiser, decoding Amazon's 16 Leadership Principles, and mastering the art of answering Bar Raiser questions. By the end, you'll be well-prepared to navigate this unique interview format and make a lasting impression on your Amazon interviewers.

Amazon's Bar Raiser Interview: A Comprehensive Guide to the Process

An Associate Product Manager assists Product Managers with their work by doing market research, gathering quantitative product data, and interpreting customer research to enable product managers to operate more efficiently and effectively. Associate Product Managers may also take on the responsibility of the development of new products, features, and product strategies to assist more senior product managers. For more information on similar roles, check out the Meta Product Manager and Amazon Product Manager guides.

In terms of day-to-day tasks, associate product managers perform all of the duties of a product manager, just on a smaller scale. In other words, while you may not be in charge of product strategy or roadmap, you will be in charge of project priorities. You may not be responsible for presenting product ideas across the company, but you will be in charge of keeping your peers and boss up to date.

The following interview guide will take you through the process of interviewing as an Associate Product Manager at Google.

The interview proceeds in the same manner as any other interview. It all starts with an application on Google's career page or through LinkedIn. If you are chosen as a potential candidate, you will go through the following steps:

Please keep in mind that you will only be eligible for the subsequent rounds if the recruitment team selects you as a suitable candidate.

Get ready for your Google Associate Product Manager interview with Prepfully's comprehensive interview guide. Our guide is filled with expert tips and strategies to help you ace your interview and land your dream job at Google.

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Google Associate Product Manager Interview Guide | Prepfully

Detailed, specific guidance on the Google Associate Product Manager interview process - with a breakdown of different stages and interview questions asked at each stage

Google Associate Product Manager Interview Guide

As a Machine Learning Engineer at Google, you would work on building and improving the algorithms and systems that power many of Google's products and services. Your responsibilities may include developing and implementing machine learning models, analyzing large datasets, and designing and running experiments to evaluate the performance of machine learning systems.

In addition to technical skills, Google values strong communication and collaboration skills. As a Machine Learning Engineer, you would work closely with other engineers, data scientists, and product managers to understand user needs and develop solutions that meet those needs. 

Google's machine learning engineers work in various areas of the company, each focusing on improving different aspects of Google's products and services. For example, a Software Engineer, Machine Learning would work on developing and scaling machine learning systems for various Google products and services. In contrast, a Machine Learning Engineer, Google Health would focus on developing machine learning models and systems to improve healthcare outcomes. A Machine Learning Engineer, Search Ranking would work on developing and optimizing machine learning models that improve Google's search results. Meanwhile, a Research Scientist, Machine Learning would be responsible for conducting research in machine learning and developing new algorithms and models to improve Google's products and services. 

These are just a few examples of the Machine Learning Engineer positions available at Google. The specific responsibilities and qualifications for each position may vary, so you should review the job descriptions carefully. Don't miss the Amazon Machine Learning Engineer and Meta Machine Learning Engineer guides for comprehensive preparation.

How to Apply for a Machine Learning Engineer Job at Google?

To apply for a Machine Learning job at Google, you will need to visit Google's career website and search for open Machine Learning positions. Once you have found a position that you are interested in, you will be able to submit an application online. One tip regarding your resume - make a few tweaks for the position and the role you are applying for which will help you have a better chance compared to other candidates. 

For example, a Software Engineer, Machine Learning would work on developing and scaling machine learning systems for various Google products and services. In contrast, a Machine Learning Engineer, Google Health would focus on developing machine learning models and systems to improve healthcare outcomes - you can highlight any past experience related to the type of MLE role you are applying for. 

If you're not sure how to do that, Prepfully offers a resume review service, where actual recruiters from Google will give you feedback on your resume.

As a part of the Google MLE interview, the candidate will need to go through multiple interview rounds:

1.  Phone Screening - The phone screening will be a conversation with a recruiter, detailing your ML background, your past relevant projects, and a quick assessment of your skill sets based on your resume.

2. Second Round of Interviews - The second round of the interview process is an extensive evaluation of your technical and professional skills. This interview round consists of multiple rounds designed to assess different aspects of your expertise and capabilities. 

3. Onsite Interview Rounds - The final primary round is an onsite interview process that consists of several rounds consisting of HR and VP interviews along with DSA round and ML System Design round.

Detailed, specific guidance on the Google Machine Learning Engineer interview process - with a breakdown of different stages and interview questions asked at each stage

Google Machine Learning Engineer Interview Guide

Google Software Engineers are responsible for designing, developing, testing, deploying, maintaining, and improving software used literally by billions of users. There is an expectation to be clearly "beyond the average", and this is reflected in a challenging interview process. 

As a minimum expectation, you're expected to be extremely competent at coding (the language itself doesn't particularly matter), and in writing this elegantly, readably and robustly. If you're interviewing for a more senior role, you're also expected to be good at architecting large scale systems which work reliably and predictably in solving for user needs. For similar opportunities, refer to the Netflix Software Engineer and Spotify Software Engineer guides. And finally - Google has a strong preference for candidates who fit well within their culture, and make no secret of this fact. If you're a brilliant a** -- it's unlikely you'll receive an offer.

The interview process is designed to filter "in" candidates who meet this bar.

The Google Software Engineer interview consists of 3 rounds.

Round 1: Recruiter screen. Short discussion, mostly to filter out those who clearly don't meet the bar in experience, relevant skills, motivations etc

Round 2: Technical phone screen. These are largely Coding/DSA (Data Structures and Algorithms) style interviews.

Round 3: Onsite loop. This includes 4-5 interviews with increasing difficulty as you interview for more senior roles. Junior/entry roles over-index on coding skills, and more senior roles on system design and architecture. One of the rounds will always be behavioral.

Detailed guidance on the Google Software Engineer interview process - with a breakdown of different stages + interview questions asked at each stage, and deepdives on Google-specific interview expectations such as Googleyness.

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Prepare for Google Software Engineer Interview with current Google SWE

At Google, User Experience (UX) is driven by diverse teams comprising UX Designers, Researchers, Writers, Content Strategists, Program Managers, and Engineers. Google places great importance on its users, and the UX team plays a vital role in gathering insights into people's attitudes, emotions, and behaviors to inspire and guide the design process. 

Google Interaction Designers closely collaborate with the UX team, engineering, and product management to create industry-leading products that provide value to users and contribute to Google's success. Consider checking out the Google UX Researcher and Apple UX Designer guides for broader design insights. As an Interaction Designer, you employ user-centered design methods to craft exceptional user experiences, taking concepts from inception to realization. You are expected to leverage and evolve the Google design language to create innovative and inspiring products that captivate users.

The salary range for this full-time position is $118,000 to $172,000, accompanied by bonuses, equity, and comprehensive benefits.

The Google Interaction Designer interview process consists of the following 4 stages:

Onsite interview

Let's discuss each of these in-depth:

Unlock the Doors to Your Dream Job: Interaction Designer Interview Mastery at Google - Your Comprehensive Step-by-Step Guide

Google Interaction Designer Interview Guide