Google Machine Learning Engineer Recruitment 2024: Hiring Freshers, Apply Now!

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Google Careers 2024 hiring freshers for the Audio Machine Learning Engineer. This comprehensive beginner’s guide will walk you through everything you need to know, from the recruitment off campus drive process to the required skills, responsibilities and selection process. Discover what it takes to land a rewarding role developing solutions on Google industry leading platforms.

About Google 

A problem isn’t truly solved until it’s solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.

Google Recruitment

Job Role: Audio Machine Learning Engineer

Qualification: Bachelor’s / PhD / Master’s degree

Experience: Freshers

Batch: 2023 / 2022 / 2021 / 2020

Salary: up to ₹11 LPA

Job Location: Bangalore, Hyderabad

Last Date: ASAP

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Job Description

Google’s software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We’re looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

As a key member of a small and versatile team, you design, test, deploy and maintain software solutions.

Our team’s objective is to empower our pixels and other devices with innovative and next generation audio features, with an emphasis on achieving unparalleled accuracy and efficiency in the conversion of audio signals. We specialize in developing models for audio processing and regeneration, audio enhancement, and audio analytics for communication and other applications, optimizing, porting, customizing, and validating them on the device to elevate the performance of our pixel and devices to new height.

Google’s mission is to organize the world’s information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user’s interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people’s lives better through technology.

Google

Job Responsibilities

  • Work on machine learning (ML) projects with a primary focus on speech and audio applications, leveraging the latest techniques and approaches, particularly using Generative AI and LLM.
  • Engage in memory and performance optimization to ensure the seamless deployment of ML models on Google hardware.
  • Collaborate closely with product, research, and software teams to comprehend ML requirements and deliver solutions that meet key user experiences.
  • Work alongside tools and architecture teams to streamline the deployment, validation, and testing processes specifically tailored for Google hardware.
  • Play a pivotal role in the development of ML models fine-tuned for Google hardware devices.

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Minimum Qualifications

  • Bachelor’s degree in Electrical Engineering or Computer Science or equivalent practical experience.
  • Experience in C/C++ or Python programming and Machine Learning.

Preferred Qualifications

  • PhD or Master degree in signal processing, data science and machine learning.
  • Experience in audio, speech, and machine learning.
  • Experience in DSP and knowledge of embedded systems.
  • Excellent problem-solving, analytical, communication and teamwork skills.

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Selection Process

The Google selection process for Audio Machine Learning Engineer off campus recruitment includes the following stages:

Online Application and Screening

Visit the Google Careers page and submit your application for the relevant job role along with your resume. The recruiting team screens all applications and shortlists candidates for the next round.

Online Assessment

Shortlisted applicants are invited to complete an online coding challenge or technical assessment to demonstrate relevant skills for the role they have applied for.

Technical Interviews

Candidates who successfully complete the assessments are scheduled for one or more technical discussions focused on computer science fundamentals, database concepts, system design etc.

HR Interview

Candidates who successfully clear the technical interviews appear for a human resources interview. The HR round evaluates your overall job fitment, strengths-weaknesses, salary expectations and organizational culture alignment.

Final Selection

Candidates who clear all the previous interview rounds are made a final job offer based on interview performance, profile match, and business requirements. The offer letter includes compensation details, job location and joining date.

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How to Apply For Google

If you are interested in the Google off campus drive 2024, here is the application process to follow:

  1. Click on the “Apply here” button provided below. You will be redirected to the official career page.
  2. Click on “Apply”.
  3. If you have not registered before, please create an account.
  4. After registration, log in and fill out the application form with all the required details.
  5. Submit all relevant documents, if requested (e.g. resume, mark sheet, ID proof).
  6. Verify that all the details entered are correct.
  7. Submit the application form after verification.

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