Software Engineer III, AI/ML, Offline Ads

Google • Mountain View, CA

1d • $147,000 - $211,000

About The Position

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.

Offline Ads is a rapidly growing area which allows advertisers to grow foot
traffic in their stores and manage their Omni Goals. This is a unique
opportunity to contribute to an important aspect of this product and generate
more value/growth towards our long term strategy.

This team presents the rare opportunity to work on product facing problems while
diving deep into the highly technical stack of bidding and modeling combined
with end-to-end large-scale distributed systems in a highly complex Ads
ecosystem.

Google Ads is helping power the open internet with the best technology that
connects and creates value for people, publishers, advertisers, and Google.
We’re made up of multiple teams, building Google’s Advertising products
including search, display, shopping, travel and video advertising, as well as
analytics. Our teams create trusted experiences between people and businesses
with useful ads. We help grow businesses of all sizes from small businesses, to
large brands, to YouTube creators, with effective advertiser tools that deliver
measurable results. We also enable Google to engage with customers at scale.

The US base salary range for this full-time position is $147,000-$211,000 +
bonus + equity + benefits. Our salary ranges are determined by role, level, and
location. Within the range, individual pay is determined by work location and
additional factors, including job-related skills, experience, and relevant
education or training. Your recruiter can share more about the specific salary
range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the
base salary only, and do not include bonus, equity, or benefits. Learn more
about benefits at Google [https://careers.google.com/benefits/].

Requirements

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience programming in Python, C++, or Java.
• 1 year of experience with reinforcement learning (e.g., sequential decision making), or specialization in another ML field.
• 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• Experience with developing large-scale infrastructure.

Nice To Haves

• Master's degree or PhD in Computer Science or related technical fields.
• 2 years of experience with data structures and algorithms.
• Experience in ads serving, auctions, or bidding.
• Experience developing accessible technologies.

Responsibilities

• Write product or system development code.
• Set up modeling solutions to better understand our advertisers, predict advertiser performance, and map existing inventory and add forecasting for businesses.
• Experiment and iterate on new features, conduct data analysis while closely working with Product Managers, UX and Sales.
• Develop innovative advertiser features and recommendations for offline goals and optimize for the best user experience and engagement.
• Implement solutions using ML models, utilize ML infrastructure, and contribute to model optimization and data processing.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level