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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Program Manager, AI Data Organization - **Company:** Lila Sciences, Inc. - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $224,000.0 - $336,000.0 - **Contract:** Permanent contract - **Skills:** Training Data, Artificial Intelligence, Machine Learning, Information Technology, Data Management, Functional Programming, Data Delivery, Data Pipelines, Programming Languages, Data Generation - **Published:** July 31, 2026 - **Apply:** https://www.careerbuilder.com/job-details/technical-program-manager-ai-data-san-francisco-ca--cab01b0d-cea3-46a3-930f-8d0342632705 ## About the Role * Bachelor's or Master's degree in Computer Science, Engineering, Life Sciences, or a related field. * 8+ years of program or project management experience in the technology or life sciences field. * Proven experience leading cross-functional programs and driving them to successful completion under tight delivery timelines. * Strong analytical and problem-solving skills, with the ability to turn technical and data requirements into actionable program roadmaps. * Exceptional written and verbal communication skills; track record of producing executive-quality documents, roadmaps, and updates that drive decisions. Bonus Points For * Direct experience in AI/ML research or product organizations, ideally in a program management or research operations capacity. * Working familiarity with model training data pipelines, dataset curation, or ML evaluation workflows - sufficient to engage credibly with researchers and ask good questions. * Experience managing programs that produce standardized outputs for downstream technical consumers (e.g., model training, eval, or platform teams). * Enthusiastic about emerging technologies and experienced in driving rapid experimentation and program iteration., Analysis Skills, Artificial Intelligence (AI), Artificial Intelligence (AI) Programming Languages, Best Practices, Biology, Candidate Sourcing, Communication Skills, Computer Science, Cross-Functional, Data Management, Data Modeling, Documentation, Emerging Technology, Equal Employment Opportunity (EEO), Functional Programming Languages, Leadership, Medicine, Operating Systems, Operations Research, Presentation/Verbal Skills, Problem Solving Skills, Project Tracking, Project/Program Management, Quality Assurance, Recruiting/Staffing Agency, Research Skills, Scientific Method, Scientific Research, Team Player, Technical Leadership, Time Management, Training Data Sets, Workflow Analysis, Writing Skills ## Description Lila is building toward scientific superintelligence, which depends on a steady supply of high-quality, purpose-built AI data. We're looking for a Senior or Principal Technical Program Manager to join our AI Research team to drive multiple AI data generation and curation workstreams - standing up new project teams, keeping them on schedule, and incorporating that data into the model training pipeline. You don't need to be an ML researcher, but you must be genuinely curious about how AI data fuels model development and able to clearly articulate what your programs will deliver. The successful candidate thrives in ambiguity, communicates exceptionally well across audiences, and knows how to build clarity and momentum on a fast-paced, rapidly scaling team. What You'll Be Building * Launch and operate cross-functional project teams that produce AI data for scientific superintelligence, ensuring each team executes with at high velocity and delivers standardized outputs the model training team can directly consume. * Serve as the key communication interface between project teams and the research, science, and model training organizations; set up the organizational information flows that allow this communication to happen with speed at scale. * Drive accountability across distributed, cross-functional teams without relying on direct authority; build consensus through clear communication and sound judgment. * Define and enforce data delivery standards, QA gates, and handoff protocols so model training receives consistent, high-quality inputs across all active project teams. * Implement best practices for rapid experimentation and iteration, enabling new project teams to ramp efficiently as additional data initiatives come online. * Develop clear documentation and reporting to communicate vision, track progress, and align project team work with broader AI Research priorities; represent program status and risks accurately even when the picture is uncertain or evolving. ## Related Videos - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Implementing continuous delivery in a data processing pipeline](https://www.wearedevelopers.com/videos/73-implementing-continuous-delivery-in-a-data-processing-pipeline) - [Fireside Chat: Deep Learning, Deep Impact: Harnessing AI for Language Innovation](https://www.wearedevelopers.com/videos/612-fireside-chat-deep-learning-deep-impact-harnessing-ai-for-language-innovation) - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [Exploring 5 Key Applications of AI Abundance with Blockchain Assurance](https://www.wearedevelopers.com/videos/971-exploring-5-key-applications-of-ai-abundance-with-blockchain-assurance) - [Big Business, Big Barriers? Stress-Testing AI Initiatives.](https://www.wearedevelopers.com/videos/1022-big-business-big-barriers-stress-testing-ai-initiatives) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)