Top Tech Jobs & Startup Jobs in London

Leads Encord Data Labs’ physical AI research communications program by identifying research topics, collaborating with ML teams and customers, shaping technical findings into publications, and managing the publishing and distribution process. The role requires hands-on ML knowledge, technical writing credibility, Python proficiency, and familiarity with computer vision, robotics, and multimodal data. Success includes measuring research impact through citations, engagement, researcher follow-ups, and inbound interest from physical AI teams.

Leads and develops a team of Commercial Associates through coaching, pipeline management, hiring, onboarding, prospecting, and deal support. Owns meeting and pipeline targets, improves campaigns and sales processes, partners with Sales, Marketing, and Customer Success, and supports team members' progression into Account Executive roles. The role also helps scale the commercial associate program and engages directly with technical prospects and key accounts.

Own and expand a portfolio of North American B2B SaaS accounts, driving adoption, upsells, cross-sells, renewals, and long-term customer value. Build relationships with technical and executive stakeholders, lead account planning and QBRs, forecast pipeline in CRM tools, identify growth opportunities, and communicate customer insights to Product and Engineering. Help establish Encord’s post-sales and expansion processes across North America.

Design, build, deploy, and operate production infrastructure for computer vision and multimodal machine learning models. Responsibilities include model serving, inference optimization, GPU utilization, distributed processing, product integration, reusable platform abstractions, monitoring, reliability, and translating research prototypes into scalable customer-facing features.

Conduct original research in robotics, computer vision, and multimodal machine learning, focusing on data curation, annotation, evaluation, and quality control. Develop hypotheses, experiments, and end-to-end prototypes for agentic multimodal workflows, video understanding, and 3D applications. Collaborate with ML and product engineering teams to integrate successful research into the platform, shape research strategy, mentor colleagues, and publish findings.

Build and deploy production software for complex customer data, machine learning, and application environments. Own system design, deployments, integrations, backend services, APIs, data workflows, and product functionality end to end. Work directly with customers and engineering teams, debug production issues, create reusable tooling, communicate technical trade-offs, and feed deployment insights into product and engineering roadmaps.

Own Encord Platform messaging across use cases, verticals, and personas. Develop positioning, value propositions, customer stories, sales enablement, website content, campaigns, and event materials. Partner with product, engineering, sales, and growth marketing teams to refine offerings, support go-to-market plans, and engage enterprise AI customers. Serve as a technical platform expert, including presenting and demonstrating products to prospects and at events.

Design, build, deploy, and own high-performance distributed data systems processing petabytes of robotics data and billions of items. Develop performant protocols and APIs, ensure reliability under heavy load, manage production services, and improve systems through testing, monitoring, code reviews, and careful architectural decisions. Collaborate with a high-performing team while solving complex data-intensive problems for AI and robotics applications.

Lead product strategy and roadmap for Encord’s AI data platform, spanning core platform, data curation, and exploration. Manage and develop Product Managers, establish product craft standards, conduct customer discovery, and translate enterprise needs into product bets. Partner with Engineering, Design, Sales, and Customer Success to deliver features, drive adoption, expansion, and customer outcomes while building a high-performing product culture.

Build and own high-performance distributed data systems supporting multimodal AI workloads. Responsibilities include designing, deploying, monitoring, and scaling storage, indexing, querying, processing, protocols, and APIs. The role requires production service ownership, sound architectural judgment, performance optimization, reliability engineering, and mentoring through code reviews, pairing, and knowledge sharing.