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Skyfall AI

Project Manager - Singapore

Posted Yesterday
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In-Office
Singapore, SGP
Senior level
In-Office
Singapore, SGP
Senior level
Manage LLM-focused research projects: translate research goals into roadmaps, coordinate PhD researchers and research engineers, oversee data curation, experiment protocols, benchmarking, budgets, risk mitigation, documentation, and external academic/industry collaborations to drive publications and product integration.
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Project Manager at Skyfall AI

Job Overview:

Skyfall AI is seeking an experienced Project Manager with a strong technical background and a passion for artificial intelligence research for our research team. This role focuses exclusively on managing advanced research projects in large language models, coordinating activities among Research, PhD-level researchers and Research SDEs . You will be responsible for translating complex research objectives into structured project plans, managing cross‑disciplinary timelines and budgets, and ensuring that cutting‑edge AI experiments move seamlessly from concept to publication and eventual product integration.

Key Responsibilities:

Research Roadmap & Milestone Management:

  • Collaborate with Research Manager to define a detailed, multi‑phase research roadmap for AI projects that includes clearly defined milestones (e.g., dataset curation, model pre‑training, fine‑tuning experiments, evaluation benchmarks, and publication deadlines)

  • Develop and maintain a centralized project dashboard to track progress across multiple research initiatives and ensure alignment with strategic goals

Cross‑Functional Team Coordination:

  • Serve as the primary liaison among PhD researchers, RSDEs and data scientists, to ensure smooth knowledge transfer and integration of research outputs.

  • Organize regular cross‑disciplinary meetings (e.g., sprint reviews, research seminars, and brainstorming sessions) to address technical challenges, adjust priorities, and drive iterative improvements in performance of models

Data, Experimentation, and Benchmark Oversight:

  • Oversee the end‑to‑end process of data curation and preparation for LLM training and evaluation, ensuring that high‑quality datasets are maintained and updated

  • Work with technical leads to design and monitor rigorous experimental protocols—including A/B tests, performance benchmarks, and error analysis—to assess model improvements and scalability

Budgeting, Risk Management, and Compliance:

  • Manage project budgets, allocate resources, and negotiate vendor or academic partner contracts when necessary

  • Identify potential risks (e.g., delays in data acquisition, model performance variance, publication bottlenecks) and implement proactive mitigation strategies while ensuring compliance with institutional and regulatory research standards

Documentation, Reporting & External Collaboration:

  • Ensure that all research activities are thoroughly documented, from initial project proposals through to published papers and technical reports

  • Prepare regular progress reports and executive summaries that translate technical research developments into actionable insights for senior leadership and potential external stakeholders (e.g., grant agencies, publication committees)

  • Facilitate partnerships with academic institutions and industry consortia to promote collaborative research and co‑authorship opportunities

Minimum Qualifications:

  • Proven track record managing high‑impact AI research projects, particularly those focused on LLM development

  • Hands-on experience leading diverse teams of PhD researchers, data scientists, and RDSEs

  • Demonstrated experience in establishing experimental protocols for model training, fine‑tuning, and performance evaluation

  • Proficiency with research‑oriented project management and collaboration tools to ensure robust tracking of research progress and reproducibility of experiments

  • Strong ability to facilitate collaboration across academic and industrial partners to drive research innovations

Location - Singapore

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