refresh

Trending companies

Trending companies

Google
Google

Organizing the world's information and making it universally accessible.

Software Engineer, AI/ML, PhD, Early Career

RoleMachine Learning
LevelMid Level
WorkOn-site
TypeFull-time
Posted1 month ago
Apply now

About the job

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.

AI in the Gemini Era is data-centric: the quality of the data used for training, fine-tuning, or RAG, matters more to the performance of the end product than almost anything else.

Our mission is to improve the quality of models that Google releases through its various product offerings by providing tools and services for making faster and easier to reach model quality goals. We do so by bringing data optimization techniques to a broad audience through integrated tools and platforms. We build and iterate tools to automatically and efficiently apply data optimization techniques. We demonstrate to our users which ones work best for their use case, and deliver insights on how to improve further. We’re working with key product teams across Google.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

  • Help scaling data optimization techniques improving the performance and quality of ML models.

  • Work closely with our Research teams as well as ML practitioners to identify, build and iterate on engineering tools, processing pipelines, data optimization techniques.

Minimum qualifications

  • Currently enrolled in or graduated from a PhD program.

  • Research experience in Artificial Intelligence, Distributed Systems, Machine Learning, Data Mining, Natural Language Processing, Image Classification, Spam Fighting, or related fields.

  • Experience in computer science and software design.

Preferred qualifications

  • Experience working with Generative AI.

  • Experience with data structures and algorithms.

  • Knowledge of Python programming.

Total Views

1

Total Apply Clicks

0

Total Mock Apply

0

Total Bookmarks

0

About Google

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

10 reviews

4.5

10 reviews

Work-life balance

3.2

Compensation

4.3

Culture

4.1

Career

4.2

Management

3.8

82%

Recommend to a friend

Pros

Great benefits and perks

Innovative and interesting work

Career development and learning opportunities

Cons

High pressure and expectations

Long hours and heavy workload

Fast-paced and overwhelming environment

Salary Ranges

57,503 data points

Junior/L3

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

L3

L4

L5

Junior/L3 · Data Scientist L3

0 reports

$176,704

total per year

Base

-

Stock

-

Bonus

-

$150,298

$203,110

Interview experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer rate

44%

Experience

Positive 0%

Neutral 56%

Negative 44%

Interview process

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense