Software Engineer, macOS Core Product - Rialto, USA
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to their customers for diverse use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to gain visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Software Engineer, macOS Core Product - Waco, USA
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability, and design and implement solutions to address the highest priority issues.
Software Engineer, macOS Core Product - Delhi, India
Work alongside machine learning researchers, engineers, and product managers to bring the AI Voices to their customers for a diverse range of use cases; deploy and operate the core ML inference workloads for the AI Voices serving pipeline; introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models; build tools to provide visibility into bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues.
Software Engineer, macOS Core Product - Mumbai, India
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to increase visibility into bottlenecks and sources of instability, then design and implement solutions to address the highest priority issues.
Software Engineer, macOS Core Product - Chennai, India
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Enterprise Account Executive - Italy
The AI Outcomes Manager will partner with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on Glean. They will lead strategic reviews and advise customers on their AI roadmap to ensure maximum value from Glean's platform. The role involves translating business needs into clear problem statements, success metrics, and practical AI solutions while collaborating with Product and R&D to shape priorities. They will conduct discovery workshops, scope pilots, and guide rollouts to drive broad and deep adoption of the Glean platform. Additionally, they will design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. The manager will proactively identify expansion opportunities and drive engagement across teams and functions.
Senior AI Engineer - San Mateo, CA
The role involves training, evaluating, and monitoring new and improved LLMs and other algorithmic models. The engineer will test and deploy content moderation models in production and iterate based on real-world performance metrics and feedback loops. They are expected to develop medium to long-term vision for content understanding-related R&D, collaborating with management, product, policy & operations, and engineering teams. The position requires taking ownership of results delivered to customers, advocating for changes in approach where needed, and leading cross-functional execution.
MCP & Tools Python Developer - Agent Evaluation Infrastructure
Developing and maintaining MCP-compatible evaluation servers, implementing logic to check agent actions against scenario definitions, creating or extending tools that writers and QAs use to test agents, working closely with infrastructure engineers to ensure compatibility, and occasionally helping with test writing or debug sessions when needed.
MCP & Tools Python Developer - Agent Evaluation Infrastructure
Developing and maintaining MCP-compatible evaluation servers; implementing logic to check agent actions against scenario definitions; creating or extending tools that writers and QAs use to test agents; working closely with infrastructure engineers to ensure compatibility; occasionally helping with test writing or debug sessions when needed.
Senior AI/ML Engineer
The Senior AI/ML Engineer is responsible for designing and implementing autonomous agents capable of task decomposition, reasoning, and self-correction, building systems that enable complex multi-step agentic workflows. They develop robust interfaces for large language models (LLMs) to interact with external APIs, databases, and financial tools, ensuring reliable function calling and accuracy within the spend-to-pay ecosystem. They lead the integration of advanced LLMs, focusing on Retrieval-Augmented Generation (RAG) and long-term memory management for high-stakes financial decision-making. Additionally, they architect and manage MLOps pipelines including continuous integration, continuous delivery (CI/CD), model serving, monitoring, and automated retraining to ensure the reliability, scalability, and efficiency of ML services. They also collaborate cross-functionally with product managers, software engineers, and data scientists to translate business requirements into technical solutions and integrate AI/ML models into core platforms.
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