Senior Software Engineer, AI/ML GenAI, Google Cloud AI - Google
Kirkland, WA 98033
About the Job
Minimum qualifications:Bachelor’s degree or equivalent practical experience.5 years of experience with software development in one or more programming languages, and with data structures/algorithms.3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.3 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).Preferred qualifications:Master's degree or PhD in Computer Science or related technical field.1 year of experience in a technical leadership role.Experience developing accessible technologies.
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 Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries.
We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community.
We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.
The US base salary range for this full-time position is $161,000-$239,000 + bonus + equity + benefits.
Our salary ranges are determined by role, level, and location.
The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations.
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 Write and test product or system development code. Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains.
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 Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries.
We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community.
We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.
The US base salary range for this full-time position is $161,000-$239,000 + bonus + equity + benefits.
Our salary ranges are determined by role, level, and location.
The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations.
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 Write and test product or system development code. Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains.
Source : Google