Senior Software Engineer, AI/ML, Traffic AI
- linkCopy link
- emailEmail a friend
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development with Python and C++.
- 5 years of experience with machine learning, artificial intelligence, or a related field.
- Experience with common machine learning frameworks such as TensorFlow or PyTorch.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Experience with large-scale data processing, data analytics, and end-to-end debugging in a production environment.
- Proficiency in Python, TensorFlow, and C++.
- Expertise in applied machine learning, including neural network architecture, model tuning, and loss function design.
- Ability to translate abstract product problems into concrete ML formulations.
- Excellent communication skills and a passion for solving user-facing problems.
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.
The Traffic AI team builds the core machine learning models that provide accurate, real-time travel time and traffic information to over a billion users worldwide. Our work is central to the Google Maps experience, influencing how people navigate their world every day across our consumer, auto, and enterprise products.
As a creative, product-focused Machine Learning Engineer, you will solve complex, real-world user problems. You will take end-to-end ownership of challenges, translating ambiguous issues into clear machine learning formulations. You will manage the full lifecycle of model development.
In this role, you will work with massive, real-time datasets to debug complex pipelines and collaborate closely with product, research, and infrastructure teams. Your work will directly improve ETA accuracy and routing for millions of users daily.
The Geo team is focused on building the most accurate, comprehensive, and useful maps for our users, through products like Maps, Earth, Street View, Google Maps Platform, and more. Every month, more than a billion people rely on Maps services to explore the world and navigate their daily lives.
The Geo team also enables developers to use the power of Google Maps platforms to enhance their apps and websites. As they plot a course for the future of mapping, they are solving complex computer science problems, designing beautiful and intuitive product experiences, and improving our understanding of the real world.
The US base salary range for this full-time position is $166,000-$244,000 + 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.
Responsibilities
- Take end-to-end ownership of user-facing issues, translating ambiguous problems into clear machine learning formulations.
- Drive the full lifecycle of model development, from data processing and featurization to designing and tuning neural network architectures.
- Search into large-scale, real-time production data to diagnose issues, identify data quality problems, and debug the entire data-to-model pipeline.
- Design and execute robust offline and online experiments to validate model performance and its impact on product metrics.
- Collaborate closely with Research, Infrastructure, and Product teams to innovate and deliver solutions that improve navigation for millions of users.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.