Senior Staff Software Engineer, Machine Learning, ML Training

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’s revolutionary Cloud TPUs were designed from the ground up to accelerate machine learning workloads, providing the computational power to train and run machine learning models in a fraction of the time and cost conventionally required. With the new Google Cloud Platform (GCP) Cloud TPU service and Google Kubernetes Engine (GKE) support, it's easy to take your existing ML workloads on leading ML frameworks (PyTorch and JAX) and move them to the cloud to take advantage of this great capability.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits Learn more about benefits at Google . Build and deliver ML frameworks to perform training at LLMS and stable diffusion models for Google Cloud customers. Design and implement AI frameworks software for ML workloads in the cloud that enables models for language modeling, stable diffusion, rankings and recommendations, etc. Identify and resolve issues in software, performance, and topology. Work closely with software engineers, product managers and other engineering teams to get high-quality products and features through the software project lifecycle. Design, develop, test, deploy, maintain, and improve software. Minimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience in software development (e.g., Python). 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 5 years 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. 5 years of experience with design and architecture; and testing/launching software products. 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. 5 years of experience in a technical leadership role leading project teams and setting technical direction. Experience with ML modeling and scaling. Experience with large scale distributed systems or machine learning systems (Training for LLM, image generation). Experience with building cloud based services, including with GCP. Bachelor’s degree or equivalent practical experience. 8 years of experience in software development (e.g., Python). 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). 5 years 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. 5 years of experience with design and architecture; and testing/launching software products.