Software Engineer, macOS Core Product - Dortmund, Germany
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 architectures to improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability, then design and implement solutions to address the highest priority issues.
Software Engineer, macOS Core Product - Nuremberg, Germany
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 machine learning 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 design and implement solutions to address the highest priority issues.
Software Engineer, macOS Core Product - Hanover, Germany
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate core ML inference workloads for AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability and design and implement solutions for high 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.
Sr AI Engineer | Remote - Europe | TS/Vue/NodeJS
As a Senior AI Engineer, you will drive intelligent features that redefine how users build automations by building AI-powered capabilities such as natural language input and smart suggestions to make creating workflows faster and more intuitive. You will collaborate across engineering, product, and design to integrate generative AI and LLM-based enhancements into the core user experience, improve existing AI integrations, develop new ones, and shape how AI powers the product. Responsibilities include architecting and implementing AI-powered capabilities like code generation, intelligent node creation, and workflow optimization; integrating LLM APIs and embedding models for text-to-workflow and natural language code suggestions; designing and iterating on prompts to improve model output and user experience; building internal tooling, evaluation benchmarks, and automated testing for AI components; collaborating closely with other engineers to ensure AI features are reliable, performant, and scalable; balancing experimentation with impact by shipping quickly with a focus on user value; and staying current with advances in LLMs, prompt frameworks, and developer tools to inform the product roadmap.
Forward Deployed Engineer - Berlin
Lead customer discovery and design sessions to map business processes, identify automation opportunities, and define solution architecture. Design, build, and deploy integrations using low/no-code platforms (Zapier, Make, n8n, Workato) and CRM automation tools (HubSpot Workflows, Salesforce Flow) with API connectors. Collaborate with Engineering to validate technical feasibility, resolve blockers, and share field learnings that inform product improvements. Configure and optimize the AI Agent defining intents, prompts, actions, guardrails, and performance metrics. Manage complex, cross-functional deployments by defining timelines, aligning stakeholders, ensuring accountability, and delivering on time and within scope. Create scalable models and reusable frameworks (templates, playbooks, reference architectures) that make future projects faster and more consistent. Champion continuous learning and enablement by training peers, running internal workshops, and documenting best practices to raise the technical bar across the team. Run global, targeted outbound campaigns within the existing customer base to generate pipeline and accelerate adoption, working closely with the customer marketing team. Collaborate with GTM leadership to embed routines and cadences that drive accountability for new product pipeline, forecast accuracy, and performance tracking. Own regional top-line targets for assigned products by collaborating with Account Executives and Account Managers who hold add-on quotas. Act as an internal product owner within the GTM function by defining product-specific MRR strategies, coordinating cross-functional support, and ensuring Aircall delivers the leading AI-enabled communication platform. Collaborate with Product and PMM to shape the AI Voice Agent roadmap based on customer needs, integration insights, and field learnings. Drive internal and external product education, including enablement for System Integrators and channel partners. Maintain deep awareness of AI and CX industry trends, ensuring Aircall's positioning remains competitive and insights continuously feed back into product and GTM strategies.
AI Research Scientist - Vision-guided robotics
As a Senior AI Research Scientist for Vision-guided robotics at Intrinsic, you will lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Your work will involve creating models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. You will collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities that can be deployed on physical hardware for industrial applications. Responsibilities include researching and developing deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios, designing algorithms for robots to manipulate complex or deformable objects with high precision, collaborating with software engineers to optimize and deploy research prototypes onto robotic hardware, evaluating model performance in simulation and real-world environments to ensure robustness and reliability, identifying opportunities to apply state-of-the-art advancements in computer vision and robot learning to industrial problems, mentoring junior researchers, and contributing to the technical direction of the manipulation research roadmap.
Senior Software Engineer, ML Ops & Infrastructure
As a Senior AI Research Scientist for Vision-guided robotics, you will lead the research and development of novel deep learning algorithms enabling robots to perform complex, contact-rich manipulation tasks. You will explore the intersection of computer vision and robotic control, designing systems for robots to perceive and interact with objects in dynamic environments, creating models that integrate visual data to guide physical manipulation beyond simple grasping. Collaborating with a multidisciplinary team, you'll translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. You will research and develop deep learning architectures for visual perception and sensorimotor control, design algorithms for manipulation of complex or deformable objects with high precision, collaborate with software engineers to optimize and deploy prototypes onto robotic hardware, evaluate model performance in simulations and real-world environments to ensure robustness, identify opportunities to apply advancements in computer vision and robot learning to industrial problems, and mentor junior researchers contributing to the technical direction of the manipulation research roadmap.
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