Staff Software Engineer, AI/ML, ML Infrastructure, Search Ads

Responsibilities

You will design, develop, and maintain machine learning infrastructure while collaborating with research teams to optimize modeling techniques. The role involves analyzing performance, improving system robustness, and prototyping new workflows to support large-scale advertising technology.

Requirements

Candidates must have at least 8 years of programming experience in Python or C++ and 5 years of experience in machine learning design and deployment. A bachelor's degree is required, with preference given to those holding a master's or PhD in a technical field.

Skills

• Python
• C++
• Machine Learning
• Model Deployment
• Model Evaluation
• Data Processing
• Debugging
• Fine Tuning
• Software Design
• Architecture
• Generative AI
• Large Language Models
• Computer Vision
• Distributed Computing
• Information Retrieval
• System Design

Benefits

• Bonus
• Equity

About this role

MINIMUM QUALIFICATIONS:

* Bachelor’s degree or equivalent practical experience.
* 8 years of experience programming in Python or C++.
* 5 years of experience leading ML design and optimizing end-to-end Machine
Learning (e.g., model deployment, model evaluation, data processing,
debugging, fine tuning).
* 5 years of experience testing, and launching software products.
* 3 years of experience with software design and architecture.
* 2 years of experience with GenAI techniques (e.g., large language models,
multi-modal, large vision models) or with GenAI-related concepts (e.g.,
language modeling, computer vision).

PREFERRED QUALIFICATIONS:

* Master’s degree or PhD in Engineering, Computer Science, or a related
technical field.
* 8 years of experience with data structures and algorithms.
* 3 years of experience in a technical leadership role leading project teams
and setting technical direction.
* 3 years of experience working in a complex, matrixed organization involving
cross-functional or cross-business projects.

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.

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

Google Ads is at the forefront of AI innovation, applying cutting-edge machine
learning and Generative AI models like Gemini to power a multi-billion dollar
global business.

Our work directly impacts billions of users by protecting users from harm,
improving ad quality, and optimizing campaigns for advertiser
return-on-investment. We foster a culture of deep collaboration, partnering
closely with teams like Google Research and DeepMind to solve complex
challenges. Join us to work on state-of-the-art AI, take on problems at an
unparalleled scale, and build the next generation of advertising technology.

Individual pay is determined by factors including job-related skills,
experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google
[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

* Work across many different aspects of machine learning infrastructure and
modeling. 
* Support new modeling techniques and products for changing infrastructure
(training and serving). Prototype new infrastructure, automation, workflows,
and tooling.
* Analyze and debug performance, and make improvements. Improve robustness,
reliability, usability of infrastructure.

* Collaborate closely with other members of our team and partners to build
systems that take advantage of and integrate seamlessly across our ecosystem.
Engage with modeling teams to explore pain points and novel use cases.
* Research emerging technology and make trade-off decisions on immediate wins
vs longer-term stability.

About Google

Software Development · 10,001+ employees · headquartered in Mountain View, CA