New job, posted less than a week ago!
Job Details
Posted date: Mar 16, 2026
Location: Kirkland, WA
Level: Senior
Estimated salary: $179,000
Range: $147,000 - $211,000
Description
Design and implement production-grade Generative AI models to enhance the Google Meet. Optimize Large Language Models (LLMs) for real-time collaboration. Scale ML inference to work efficiently across different client environments (e.g., Web, Android, iOS) and server-side infrastructures, ensuring low latency and high reliability. Collaborate with Product and UX teams to prototype and productionalize great user experiences, taking features from initial paper research to global rollout. Write clean, maintainable, and highly-performant code in C++, Python, or Java, adhering to Google’s engineering standards. Develop robust data pipelines for training, fine-tuning, and evaluating models, ensuring data privacy and security protocols are strictly followed.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 $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.
Qualifications
Minimum qualifications: Bachelor’s degree or equivalent practical experience.2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
1 year 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 a related technical field. 2 years of experience with data structures and algorithms. Experience developing accessible technologies.
Extended Qualifications
Bachelor’s degree or equivalent practical experience.2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).