GOOGLE Hiring Software Engineer, Machine Learning in India Salary starts from ₹12,20,294/year Apply Online.

Company:	GOOGLE
Job Role:	Software Engineer, Machine Learning.
Experience:	(1-5 years).
Vacancy:	25+
Qualification:	Bachelor's Degree in Computer Science, Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning or related technical field.
Salary:	₹12,20,294/year.
Location:	Bangalore, Karnataka, India.
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Apply Mode:	(Online)
Deadline:	Not Mentioned

About the Company:

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We need products that handle information on a massive scale and go beyond web search. We're looking for engineers with expertise in a wide range of areas, including information retrieval, distributed computing, large-scale system design, networking, data storage, security, artificial intelligence, natural language processing, UI design, and mobile; the list goes on and on. In this role, you will work on a specific project critical to Google's needs. As you and our fast-paced business grow, you will have opportunities to switch teams and projects. We need engineers who are versatile, display leadership qualities, and are eager to tackle new problems across the full stack as we push technology forward.

You will manage project priorities, deadlines, and deliverables using your technical expertise. As a software developer, you will design, develop, test, deploy, maintain, and enhance software solutions.

Software Engineers get to choose from a wide variety of projects, such as building signals and models for detecting bad users and rejecting fraudulent and abusive contributions, building tools for Google operators to provide labels for model training, and building the infrastructure on which all of these operate. As well as programming skills, you will develop intuition for open ended problems and learn how Machine Learning can be applied to solve real world problems.

Google has always been and will always be an engineering company. Technology's greatest challenges are best met by people with broad technical skills who can make an impact on millions, if not billions, of users. The engineers at Google not only revolutionize search, but they work on massive scalability and storage solutions, large-scale applications, and entirely new platforms for developers around the world. Each new technology advancement from Google engineers changes the world, whether it is Google Ads, Chrome, Android, YouTube, Social or Local.

Responsibilities:

• Develop, test, deploy, maintain and improve machine learning models/infrastructure and software that uses these models.
• Manage project priorities, deadlines, and deliverables.
• Take part in cutting edge AI and machine learning research.
• Support large, complex web applications with libraries and frameworks.
• Contribute to the engineering process from planning and coordinating through execution and delivery of complex engineering projects.

Minimum Qualification:

• Bachelor's degree in Computer Science, or related technical field, or equivalent work experience.
• Work experience of five years or more.
• Expertise in the design and implementation of distributed software systems (e.g. Java, C++, Python).
• Expertise in artificial intelligence (AI), machine learning models, and ML infrastructure, as well as Natural Language Processing or deep learning.

Preferred Qualification:

• Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning or related technical field.
• A minimum of two years of relevant work experience in machine learning software development and architectures (with a focus on deep learning).
• Experience in the following areas: Server Backend Distributed and Parallel Systems, Full Stack Development (front end and back end), Scalable Enterprise Platforms and Applications, Application Security and Incident Management, Machine Learning, Information Retrieval, or Natural Language Processing.
• Extensive experience developing, deploying, and improving Machine Learning algorithms for real-world products.

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