Skip to main content

Senior Full Life-Cycle Recruiter specializing in AI Engineering & Applied

Posted yesterday

eliassen groupMadison (WI)

SENIORITY

Senior

Apply (opens in a new tab)

About the role

Description: Remote in San Francisco, CAOur 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. w2Responsibilities
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. Experience Requirements 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.
Education Requirements:

Before you apply

Applying takes about a minute. These four things decide how fast it moves after that.

Your profile is current

It's what we read first. Occupations, seniority and locations matter more than a long history.

Two examples you can talk through

Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.

A number in mind

What you're on now and what would make you move. We negotiate better when we know both.

Your notice period

Employers plan around it, and it's the question that stalls offers most often.

Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.

More like this