Blazetalent

Blazetalent

Senior Sourcer (AI / ML / Infra) - Contract

Remote, USA · Senior

Sponsorship not specified$50k-$90kDetected 175 days ago
C++Distributed SystemsGitMachine LearningPyTorchRecruitingPower ElectronicsResearch

About the role

  • Identify "pockets of talent" within hardware-accelerated compute and distributed systems.
  • Strategic Outreach: Craft highly personalized, technical outreach that resonates with senior engineers who are inundated with recruiter spam.
  • You must speak the language of AI infra.

Responsibilities

  • Deep-Technical Sourcing: Build robust pipelines for highly specialized roles including GPU/TPU Kernel Engineers, Distributed Systems Architects, InfiniBand/RDMA Networking Specialists, and AI Platform Engineers.
  • High-Velocity Delivery: Maintain a high volume of qualified "first-screens" while ensuring the candidate experience is white-glove from the very first touchpoint.
  • ASAP About the Role Blaze Talent is seeking an elite Technical Sourcer to support a high-growth AI Hyperscaler client.
  • This isn't a generalist role; you will be the primary engine driving top-of-funnel talent for the teams building the massive-scale compute, networking, and power systems that make modern AI possible.
  • You will be embedded within a world-class engineering organization, hunting for the 1% of talent capable of building and scaling AI infrastructure at a global level.
  • Build robust pipelines for highly specialized roles including GPU/TPU Kernel Engineers, Distributed Systems Architects, InfiniBand/RDMA Networking Specialists, and AI Platform Engineers.
  • Maintain a high volume of qualified "first-screens" while ensuring the candidate experience is white-glove from the very first touchpoint.

Requirements

  • AI Infrastructure Expertise: Must have prior experience sourcing for AI Infrastructure, Data Centers, or Large-Scale Cloud Systems.
  • 5+ Years Sourcing Experience: A proven track record of finding "purple squirrels" in the deep-tech space, preferably with experience at a major Cloud Service Provider (CSP) or a high-growth AI startup.
  • Technical Fluency: Ability to screen candidates for proficiency in low-level programming (C++/CUDA/Rust), distributed frameworks (PyTorch/Ray), and hardware/software co-design.
  • You enjoy the challenge of finding talent that isn't looking to be found.

Nice to have

  • Mastery of LinkedIn Recruiter, GitHub, and technical sourcing extensions.
  • Experience with Ashby (ATS) is a significant plus.
  • Must be able to operate during US business hours (PST preferred).
  • This is a chance to work at the absolute center of the AI boom.
  • Our client is an industry leader providing the backbone for the next generation of LLMs.
  • If you are a sourcer who loves the "deep tech" side of the house and wants to work on a high-stakes, high-impact project, this is for you.
  • Availability: Must be able to operate during US business hours (PST preferred).

Compensation

  • $50-$90/hr Duration: 6 months (Potential for conversion) Start Date: ASAP About the Role Blaze Talent is seeking an elite Technical Sourcer to support a high-growth AI Hyperscaler client.
  • This isn't a generalist role; you will be the primary engine driving top-of-funnel talent for the teams building the massive-scale compute, networking, and power systems that make modern AI possible.
  • You will be embedded within a world-class engineering organization, hunting for the 1% of talent capable of building and scaling AI infrastructure at a global level.
  • Market Mapping & Intelligence: Map the talent landscape across competing hyperscalers, chipmakers, and specialized AI labs.
  • Identify "pockets of talent" within hardware-accelerated compute and distributed systems.
  • Deep-Technical Sourcing: Build robust pipelines for highly specialized roles including GPU/TPU Kernel Engineers, Distributed Systems Architects, InfiniBand/RDMA Networking Specialists, and AI Platform Engineers.

This listing is sourced directly from Blazetalent's careers page and normalized into a canonical job model.