Senior Technical Project Manager

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We are seeking a Senior Technical Project Manager to drive complex engineering initiatives from planning through delivery. You will translate ambitious technical objectives - such as maximizing the performance of cutting-edge AI models on specific hardware - into actionable project plans, structured execution cycles, and measurable outcomes.
This is a hands-on technical project management role rather than an administrative PM position. You will work closely with engineering teams on LLM inference optimization, GPU performance engineering, and distributed serving, while coordinating senior engineers and technical leaders across local and international teams.
Your day-to-day responsibilities may include launching optimization projects under signed statements of work with global hardware partners, balancing shared GPU cluster resources between urgent customer benchmarks and internal release testing, coordinating with partner engineering teams across time zones, and translating performance data into timely status reports that support decision-making by leadership and customer-facing teams.
Responsibilities
- Manage engineering projects end to end, from statement of work definition and project kick-off through weekly execution, progress tracking, and final performance reporting, in close collaboration with technical leads.
- Define project scope, milestones, and acceptance criteria alongside engineers, researchers, and customer-facing teams, including measurable performance targets such as throughput and latency across specific hardware configurations.
- Drive project execution and governance across the project portfolio through regular team syncs, leadership reviews, and status reporting, ensuring project progress, risks, and overall health remain visible from engineering teams to C-level leadership.
- Coordinate cross-functional and international stakeholders across local teams, overseas technical leadership, and global partners, serving as the primary point of contact for assigned projects and ensuring effective communication across time zones.
- Anticipate and manage project risks and changing priorities, including competition for shared GPU cluster resources, urgent customer benchmarking requests, and rapidly evolving model development priorities. Reassess plans, reprioritize tasks, and remove blockers to keep engineering teams focused on critical deliverables.
- Adapt agile practices to research-driven engineering environments, maintaining execution discipline and delivery momentum while accommodating evolving technical requirements and the fast pace of AI development.
- Foster a culture of ownership, transparency, and constructive technical debate, encouraging accountability, open communication, and collaborative problem-solving across teams.