Senior Technical Program Manager, Lilt

• 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
• 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)
• Technical Depth: Hands-on experience with RAG architectures, vector databases, and agentic workflows.Familiarity with Reinforcement Learning (RLHF/RLAIF) environments and preference signaling
• Scale & Quality: Demonstrated ability to manage "high-throughput" programs where quality control is mission-critical. You should have experience with automated validation at scale
• Strategic Execution: Strong business acumen and the ability to manage high-stakes stakeholder relationships with frontier AI labs
• Operational Excellence: Expert-level understanding of software integration (RESTful APIs, cloud infrastructure) and the ability to troubleshoot complex technical bottlenecks in real-time
• Adaptability: Ability to thrive in a "frontier" environment where requirements can shift based on the latest research breakthroughs

Desirable

• As a Senior TPM of Applied AI, you will sit at the intersection of cutting-edge research and industrial-scale execution
• Ou will be responsible for leading complex programs that provide the "fuel" for AI models: high-quality, high-volume data and bespoke engineering deliverables
• You aren't just managing timelines; you are architecting the workflows that ensure the next generation of LLMs and multimodal models are trained on the most accurate, diverse, and complex sourced data available
• 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
• Bespoke FDE Deliverables: Lead technical workstreams to deliver custom research and engineering improvements via the forward-deployed engineers, such as RAG (Retrieval-Augmented Generation) workflow optimizations, model evaluations, and synthetic data generation
• RL & Environment Management: Oversee projects involving Reinforcement Learning (RL) environments, ensuring the infrastructure and human-feedback loops are optimized for model alignment and performance
• Technical Consultation: Serve as the primary technical point of contact for AI researchers and engineers at partner labs, translating complex research needs into actionable engineering roadmaps
• 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
• Opportunity to work with cutting-edge AI technology in a rapidly growing industry