Member of Technical Staff, Robotics Research Lead
Lead the design and execution of the AI’s robotics research agenda, recruit, mentor, and manage a small team of research scientists and engineers in the London lab, collaborate with the world model and simulation teams to develop state-of-the-art training platforms for robotics, guide the creation of persistent 3D/4D scene representations and advanced embodied AI methodologies, drive research efforts in scene understanding, sim-to-real transfer, and advanced planning, foster partnerships with leading ML researchers, hardware specialists, and external collaborators, and help establish the lab's technical culture and external reputation.
Member of Technical Staff - Robotics Research Lead
Collaborate with the world model team to build a state-of-the-art training and simulation platform for robotics. Develop persistent 3D/4D scene representations that maintain temporal consistency. Unlock advanced robotics planning and decision making through in-house, cutting-edge world models. Ensure sensing and system dynamics perform reliably in high-stakes, real-world operations where models think, simulate, and act. Partner with ML researchers to innovate on generative models and physical AGI. Collaborate closely with ML researchers developing multimodal world models and generative systems, and with hardware teams and partners to ensure robotic platforms, sensing, and system dynamics behave optimally in real-world operation.
Senior Product Manager, Enterprise AI Platform
Define the vision and roadmap for the Enterprise AI platform. Understand key enterprise use cases and pain points through deep engagement with forward deployed teams, turning common pain points into high leverage features. Partner with research, engineering, and design teams to translate AI capabilities into useful product features. Own product lifecycle from ideation through launch.
Senior Product Manager, Enterprise AI Platform
Define the vision and roadmap for the Enterprise AI platform. Understand key enterprise use cases and pain points through deep engagement with forward deployed teams, turning common pain points into high leverage features. Partner with research, engineering, and design teams to translate AI capabilities into useful product features. Own the product lifecycle from ideation through launch.
Sr. Applied AI Engineer
As a Sr. Applied AI Engineer, you will build reusable AI products by acting as the product owner for your application area, designing, developing, and deploying robust, repeatable Generative AI agents that serve as configurable solutions for customers. You will partner with Solution and Forward Deployed Engineers during sales and implementation projects to understand customer needs, develop standard templates and reusable components to reduce time-to-activation, and solve core challenges. You will synthesize customer feedback to form a clear vision for your agents, iterate on solutions to solve concrete use cases at scale, and treat each agent as a product itself. Additionally, you will collaborate closely with the core product team to prioritize platform features that unblock application development and serve as an expert user consultant during new feature development.
Member of Engineering (Reinforcement Learning Infrastructure)
Keep up with the latest research, and be familiar with the state of the art in LLMs, RL, and code generation. Develop methods for tuning training and inference end-to-end for high throughput. Design data control systems in an RL pipeline that govern what the model sees and when. Debug cases where infrastructure decisions are silently degrading learning dynamics. Build observability tooling that surfaces when a system-level issue is the root cause of a training regression. Help build robust, flexible and scalable RL pipelines. Optimize performance across the stack — networking, memory, compute scheduling, and I/O. Write high-quality, pragmatic code. Work in the team: plan future steps, discuss, and always stay in touch.
Member of Engineering (Reinforcement Learning)
Research and experiment on ways to improve reasoning and code generation for LLMs. Own the full experiment life cycle from idea to experimentation and integration. Keep up with the latest research, and be familiar with the state of the art in LLMs, RL, and code generation. Translate research ideas into clean, reusable codebases that other researchers can build on. Design, analyze, and iterate on data generation and training of LLMs. Implement and iterate on RL training pipelines that scale reliably across domains. Diagnose training instabilities and failures, debug RL runs and propose mitigation methods. Write high-quality, reproducible and maintainable code.
VP Engineering - London
The VP Engineering is responsible for defining and executing a scalable, defensible technology strategy; building a world-class engineering organization and platform; partnering with the CEO on product direction, investor communication, and long-term vision; and ensuring the successful bridging of frontier AI research with enterprise-grade deployment. Responsibilities include architecting and scaling H's AI platform, making build vs. buy decisions, ensuring performance, reliability, and cost efficiency, establishing technical moats, translating AI capabilities into enterprise-ready products, standardizing bespoke systems, balancing iteration speed with robustness, building and leading engineering teams, scaling organizational structure, implementing quality processes, acting as a key counterpart to the CEO in board and investor discussions, articulating technology and product roadmaps, providing technical due diligence, operating cross-functionally across Research, Product, and Go-to-Market, aligning engineering with customer and revenue goals, and helping define long-term company positioning.
Parcel Contract Intelligence Consultant
Ship critical infrastructure by managing real-world logistics and financial data for the largest enterprise in the world. Own the why by building deep context through customer calls and understanding Loop’s value to customers, pushing back on requirements if a better, faster solution exists. Work across system boundaries with full-stack proficiency, including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to automate boilerplate work, focusing on quality, architecture, and product taste. Constantly optimize development loops, refactor legacy patterns, automate workflows, and fix broken processes to raise the velocity bar.
Manager, Forward Deployed Engineering - London
Lead and grow a team of Forward Deployed Engineers delivering production systems with frontier models; own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality; codify effective practices into tools, playbooks, and roadmap inputs to create leverage for OpenAI and its developer community; notice and urgently raise early indicators related to product behavior, customer environments, or delivery practices; use judgment to determine necessary actions; set high performance standards for FDEs and support individual growth through direct, actionable feedback; define staffing and support structures for scalable field teams without added complexity.
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