Senior Full Life-Cycle Recruiter specializing in AI Engineering & Applied
Full-time
Eliassen Group
Description Remote in San Francisco, CA Our client seeks a Senior Full Life-Cycle Recruiter specializing in AI Engineering and Applied Research. The recruiter will manage end-to-end hiring, advise leaders with market insights, and execute deep sourcing strategies to build inclusive pipelines. The role is remote in market for the Bay Area with occasional onsite collaboration in San Francisco. Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $ to $58.00/hr. w2 Responsibilities
- Manage full life-cycle recruiting from strategy kickoff through sourcing, screening, offer construction, negotiation, and closing.
- Partner with AI Engineering leaders and Applied Research Directors to provide market insights, talent mapping, and pipeline analytics.
- Source specialized technical talent across traditional and non-traditional channels.
- Deliver an inclusive and high-touch candidate experience that reflects our client's culture.
- Craft competitive and complex offer packages, including equity, compensation structures, and sign-on incentives, and close against competitive markets.
- Promote diversity, equity, and inclusion across pipelines and selection stages.
- 4+ years of full life-cycle recruiting experience in technology with focus on specialized engineering or scientific roles.
- 2+ years sourcing and closing candidates in AI, Machine Learning, Data Science, or Applied Research.
- Proven success managing complex offers and competing with top-tier tech companies and labs.
- Preferred: 5+ years recruiting in generative AI, LLM infrastructure, deep learning frameworks, or advanced AI research.
- Preferred: Understanding of AI ecosystem skills such as PyTorch, TensorFlow, Distributed Computing, Model Optimization, Vector Databases, and Multi-Agent Systems.
- Preferred: Experience sourcing from leading academia, research labs, and tech research conferences.
- Preferred: Analytical capability using talent analytics and ATS tools such as Workday, Greenhouse, or Beamery.
Vacancy posted 3 hours ago
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