Jobs / United Kingdom / Lilt Corporate

Senior Technical Program Manager, Applied AI

Lilt Corporate · 🇬🇧 London, UK

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  • No government sponsor record hereThis employer posted directly and does not match a government sponsor register.
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About the role

About LILT AI is changing how the world communicates — and LILT is leading that transformation. We're on a mission to make the world's information accessible to everyone , regardless of the language they speak. We use cutting-edge AI, machine translation, and human-in-the-loop expertise to translate content faster, more accurately, and more cost-effectively without compromising on brand, voice, or quality. At LILT, we empower our teammates with leading tools, global collaboration, and growth opportunities to do their best work. Our company virtues— Work together, win together; Find a way or make one; Dance in the customer's shoes; Quicker than they expect; Quality is Job 1 —guide everything we do. We are trusted by Intel Corporation , Canva , the United States Department of Defense , the United States Air Force , ASICS , and hundreds of global Enterprises. Backed by Sequoia, Intel Capital, and Redpoint, we’re building a category-defining company in a $50B+ global translation market being redefined by AI. About the Role: As a Senior TPM of Applied AI, you will sit at the intersection of cutting-edge research and industrial-scale execution. You will operate with an entrepreneurial mindset, effectively acting as the CEO of your customer's business to proactively drive success. You are responsible for leading complex benchmark transformations and data deliverables. Rather than just managing timelines, you are architecting workflows to ensure the next generation of LLMs and multimodal models are trained on the most accurate, diverse, and complex data available, while championing innovative solutions alongside our research lab partners. • Entrepreneurial Benchmark Leadership: Act as the CEO of your customer’s business by proactively proposing and co-developing benchmark transcreations directly with research lab partners, ensuring our deliverables are innovative, tailored, and aligned with their core research objectives. • Frontier Lab Program Management: Lead the end-to-end execution of high-priority technical programs for frontier AI labs, managing the delivery of massive-scale datasets and bespoke engineering milestones. • High-Volume Data Operations: Architect and oversee pipelines for delivering high-volume data samples across multiple modalities (text, image, video, audio), ensuring strict adherence to delivery cadences without sacrificing precision. • End-to-End Quality Control: Partner with production to implement rigorous, automated, and human-in-the-loop QC frameworks to ensure data integrity across various domains and languages. • Cross-Functional Leadership: Bridge the gap between forward-deployed engineering resources, research, and production teams to ensure LILT can serve the needs of the frontier AI market. Qualifications • Education: B.S or M.S. in Computer Science, AI, or a related technical field with 10+ years of industry experience. Equivalently, a Ph.D. with 5+ years of experience in a high-growth AI/Engineering environment. • Entrepreneurial Mindset: Experience founding or scaling a venture, or operating in an early-stage startup environment where you drove business growth and strategic initiatives from the ground up. • Strategic Execution: Strong business acumen and the ability to manage high-stakes stakeholder relationships with frontier AI labs. • Frontier AI Expertise: Proven track record of managing data pipelines for LLMs or multimodal models. Deep understanding of training, inference, and the nuances of data diversity (multilingual and multi-domain). • Scale & Quality: Demonstrated ability to manage "high-throughput" programs where quality control is mission-critical. You should have experience with automated validation at scale. Preferred Skills • Fluency in multiple human languages. • Profic

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Source: Arbeitnow feed First seen: 2026-10-06 Last confirmed: 2026-10-06 How our data works → Report this job

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