Research

Senior Technical Program Manager – Applied AI$180,000 – $200,000 Fully Remote (US East Coast preferred) Full-Time / PermanentA fast-growing AI language technology company is looking for a Senior Technical Program Manager to join their Applied AI team. They work with some of the world's largest organisations (including major government agencies and global enterprises) helping them translate and localise content at scale using cutting-edge AI. This is a hands-on programme management role. You will be overseeing the delivery of large datasets and custom engineering projects that are used directly to train and improve frontier AI models.Why JoinSmall, cross-functional teams where senior hires have real ownership over programmes end-to-endBacked by top-tier investors, this is a well-funded company with strong commercial tractionCompetitive base, equity, and benefitsWork that sits at the frontier of AI development, your programmes directly influence the next generation of large language modelsThe RoleYou will lead the delivery of complex technical programmes for major AI research partners. In practice, this means managing the pipelines that produce large volumes of high-quality training data - across text, audio, video, and image - and making sure that data reaches research teams accurately and on time.You will also oversee bespoke engineering workstreams, things like: retrieval-augmented generation (RAG) improvements, model evaluation projects, and synthetic data generation. You are the main point of contact for the AI researchers and engineers you work with, and you will translate their research needs into clear delivery plans.This is not a scrum master role. You need to understand what engineers are building and why, well enough to spot problems, ask the right questions, and earn the trust of technical teams on both sides.What We're Looking ForExperience managing large-scale data delivery programmes, ideally for AI or machine learning teamsA technical background. You don't need to write production code daily, but you should be comfortable reading it, reviewing it, and discussing it with engineersHands-on knowledge of modern AI concepts: training data pipelines, model evaluation, retrieval systems (RAG), and human feedback loops (RLHF)Experience working with multiple data types - not just text, but also audio, video, or image datasetsStrong stakeholder management skills at a senior levelAbility to operate in a fast-moving environment where priorities can shift with the latest research developmentsUseful but not essential:Proficiency in PythonFamiliarity with vector databases or agentic AI workflowsExperience working directly with AI research labs or frontier model teamsMultilingual backgroundWhat Success Looks LikeProgrammes delivered on time with clean, well-validated dataResearch partners feel well-supported and clearly communicated withEngineering workstreams run efficiently with minimal bottlenecksYou spot quality issues before they reach the modelTech / Domain ContextData pipelines · Multimodal datasets · RAG architectures · RLHF/RLAIF · Vector databases · Cloud infrastructure · RESTful APIs · Model evaluation