Currently tracking 489 active AI roles, up 170% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $98k–$505k (avg $233k).
| Title | Stage | AI score |
|---|---|---|
| Senior Staff Software Engineer, Machine Learning, ML Training Senior Staff Software Engineer focused on building and delivering ML frameworks for training large language models (LLMs) and stable diffusion models for Google Cloud customers. The role involves designing and implementing AI frameworks software for various ML workloads, identifying and resolving software and performance issues, and collaborating with cross-functional teams. Requires extensive experience in software development, ML design, ML infrastructure, and leading technical projects, with a focus on training ML models at scale. | DataServe | 9 |
| Senior Staff Data Scientist Manager, AI Data This role focuses on improving the quality of data used for training Machine Learning models, particularly Large Language Models (LLMs). The responsibilities include analyzing large datasets, defining data quality metrics, researching methods to enhance data quality, and influencing product direction through data insights. The role requires significant experience in data analysis and a background in quantitative fields. |
| Data |
| 8 |
| Staff Software Developer, ML Infrastructure, Core Infra Staff Software Developer focused on ML Infrastructure for Core Infra, specifically for conversational AI agents. The role involves driving technical direction for data systems, implementing scalable data solutions on GCP, and leading critical infrastructure investments to support Generative AI development. | Data | 8 |
| Software Engineer, AI/ML, PhD, Early Career Software Engineer role focused on scaling data optimization techniques to improve ML model performance and quality, working with Research teams and ML practitioners to build and iterate on engineering tools and processing pipelines. The role emphasizes the data-centric nature of AI in the Gemini era and improving model quality through data optimization. | Data | 8 |
| Software Engineer III, Google Threat Intelligence Software Engineer III for Google Threat Intelligence focused on building AI-driven systems for cyber threat collection and analysis. The role involves developing automated tools to gather data from the dark, deep, and open web, applying ML/LLMs to process unstructured text, and building data pipelines to create structured intelligence for threat databases. The goal is to enhance proactive defense against global cyber threats. | Data | 7 |
| Software Engineer, AI/ML Data and Training Infrastructure Software Engineer role focused on building and advancing ML data and training infrastructure to enable ML use cases for recommendation systems. Requires experience in software development, ML models, and ML infrastructure, including data processing, model optimization, evaluation, and deployment. | Data | 7 |
| Staff Software Engineer, ML Data Infrastructure Google's YouTube Discovery Data team is seeking a Staff Software Engineer to build and maintain large-scale data processing pipelines that power personalized discovery and ML models at YouTube. The role involves enabling next-generation model architectures and training procedures, reducing complexity in ML training infrastructure, and collaborating with other infrastructure teams. The ideal candidate will have extensive experience in C++ programming, large-scale infrastructure development, and a solid understanding of ML concepts. | Data | 7 |
| Engineering Manager, Woodshed Engineering Manager for Woodshed, a core AI/ML infrastructure team at Google, focusing on distributed systems for machine learning, dataset lakehouse management (Canon), and supporting multimodal model training for various Google product areas like Gemini and GenMedia. The role involves managing a team, contributing to product strategy, and building next-generation AI/ML systems. | DataPretrain | 7 |
| Image Processing Engineer Image Processing Engineer role focused on optimizing image quality by fine-tuning algorithms and building ML-powered tools for tuning, testing, and calibration workflows. Requires experience in image quality, computer vision, Python, and C++. | Data | 7 |
| Threat Intelligence Engineer, Cloud This role focuses on engineering and scaling systems for threat intelligence within Google Cloud. It involves designing APIs for data ingestion, developing web scrapers for dark/deep web monitoring, and architecting data pipelines that use ML/LLMs to process unstructured web content into structured intelligence. The role also includes deploying and maintaining highly available services and collaborating with threat analysts and data scientists. | DataAgent | 7 |
| Senior Software Engineer, Operations Research Senior Software Engineer role focused on developing and implementing operations research and optimization algorithms, with a component of applying machine learning methodologies to solve problems at Google scale. The role involves writing and testing code, leading design reviews, and contributing to system design and architecture. | Data | 7 |
| Software Engineer III, AI/ML, Health and Home Software Engineer III, AI/ML role focused on developing LLM-based tools for generating synthetic user data and conversations for health and home feature evaluations. This involves implementing ML solutions, utilizing ML infrastructure, and contributing to model optimization and data processing, with a focus on advancing the quality and realism of synthetic context and defining evaluation metrics. | DataAgent | 7 |
| Data Center Analytics Engineer Google is seeking a Data Center Analytics Engineer to design and implement advanced analytics, AI/ML integrations, and data visualizations. The role involves owning data engineering workstreams, collaborating on custom web applications, and engaging with stakeholders to solve business problems. The position requires a Bachelor's degree in Computer Science or equivalent experience, with 5 years in analytics and data science applications, and 5 years in data engineering. Experience with Machine Learning and AI Integrations, and web development are preferred. | Data | 5 |
| Data Engineer, Operations and Infrastructure Data Science Data Engineer role focused on designing and managing data pipelines for Vertex AI operations, building automated agents for system monitoring, and creating dashboards for efficiency metrics. The role involves collaborating with data science and finance teams to translate efficiency goals into data models and tracking systems, ensuring alignment with budgetary requirements. | Data | 5 |
| Cloud AI Engineer This role focuses on delivering big data and machine learning solutions to Google Cloud customers, acting as a technical advisor and influencing product roadmaps. It requires experience in building ML/data science solutions and software development. | Data | 5 |
| Senior Technical Program Manager, AI Data This role is for a Senior Technical Program Manager focused on AI data, managing complex projects related to data for AI models. The responsibilities include driving program outcomes, optimizing operational processes, developing tracking frameworks, and utilizing data analysis for improvements. The role requires experience with data structures or ML algorithms, and familiarity with AI/ML lifecycles and data labeling. | DataPost-train | 5 |
| Staff Software Engineer, Flume ML Staff Software Engineer at Google Cloud focused on advancing the scheduleability and auto-tuning capabilities of a planet-scale data processing infrastructure platform that powers foundational ML features and next-generation AI initiatives. The role involves technical leadership in designing, developing, and maintaining large-scale distributed systems critical for ML pipelines. | Data | 5 |
| Software Engineer, Shopping Quality Software Engineer role focused on improving data quality for LLMs within Google's Shopping Quality team. Responsibilities include writing code, design reviews, code reviews, documentation, and debugging. Requires experience with LLM data quality and preferred experience with ML models, data pipelines, and feature engineering. | Data | 5 |