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Job Details
Posted date: Jul 13, 2026
Location: Kirkland, WA
Level: Director
Description
Design, develop, test, deploy, maintain, and enhance large scale software solutions.Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.
Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.
You will lead the evolution of the Knowledge Catalog’s search experience owning the end-to-end ML lifecycle for search relevance. You will spend your days designing, prototyping, and rapidly testing advanced information retrieval techniques to ensure users can intuitively find the exact data assets they need.
You will turn search signals into intelligent features, dive deep into user query logs, click-through data, and catalog metadata to identify relevance gaps, systematically addressing them by training and tuning models that continuously elevate our core search metrics like NDCG and precision.
You will collaborate with core catalog engineers to seamlessly integrate your models into our high-throughput indexing and retrieval pipelines, ensuring that our search infrastructure remains highly scalable, robust, and capable of delivering sub-100ms response times.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Qualifications
Minimum qualifications: Bachelor’s degree or equivalent practical experience.8 years of experience in software development.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 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 ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Experience in modern ML frameworks (e.g., TensorFlow, PyTorch, or JAX).
Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures/algorithms. 3 years of experience in a technical leadership role leading project teams and setting technical direction.
3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects. Experience with modern search architectures, including two-stage retrieval systems (bi-encoders and cross-encoders), semantic search, and vector embeddings.
Extended Qualifications
Bachelor’s degree or equivalent practical experience.8 years of experience in software development.
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 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 ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Experience in modern ML frameworks (e.g., TensorFlow, PyTorch, or JAX).