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- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development, and with data structures/algorithms.
- 5 years of experience with developing Machine Learning (ML)/Artificial Intelligence (AI) algorithms and tools.
- 5 years of experience building and architecting large-scale, production quality ML systems.
- 3 years of experience in development with JAX, PyTorch, or TensorFlow.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or in a related technical field.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- 3 years of experience adapting foundation models in products with successful launches.
- Experience in the Machine Learning (ML) community through publications, open-source contributions, or conference participation.
- Understanding of foundation model training/tuning infrastructure.
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.
In this role, you will shape the future of applied Machine Learning (ML) at Google and push the boundaries of what's possible with Generative Artificial Intelligence (GenAI) technologies, leaving a lasting impact on the field. You will be building the platform to integrate SoTA GenAI-based technologies into Google's consumer-facing products. Your mission is to empower developers and researchers with cutting-edge GenAI enablement tools, driving innovation and unlocking the potential of ML across a diverse range of applications, and you will build a team to ensure the deployment of GenAI across Google is as easy, economical, and as fast as possible.
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 $189,000-$284,000 + 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.
- Drive the platform goal to incorporate fine-tuning, multi-agent systems, prompt engineering, and model optimization into the Google product development lifecycle.
- Develop and maintain Google's products, written in C++ and Python, conforms with Google-wide coding and testing standards.
- Design and implement customer requested Generative Artificial Intelligence (GenAI) features through multiple stages, requirements gathering, proposing design and building agreement among the key stakeholders, implementing and rolling out to productivity.
- Collaborate with stakeholders (including other Google product areas, Google Research, and DeepMind organizations) to identify emerging technology related to Artificial Intelligence (AI) and Generative AI, and develop a strategic plan for translating these into practical solutions for Google products.
- Provide technical leadership and mentorship to team members, fostering their growth and development in the applied Machine Learning (ML) space.
Build for everyone Since our founding in 1998, Google has grown by leaps and bounds. Starting from two computer science students in a university... Read more