Senior Recruiter, AI Labs

What You'll Be Doing & Why It Matters

Salesforce is building the AI-powered future of enterprise software — and we need a world-class recruiter to help us win the most contested talent market in the industry. This isn’t a high-volume, transactional recruiting role.

This is a strategic seat at the table for a recruiter who has spent their career deeply embedded in recruiting for one or more of the following areas; Applied Science, Machine Learning, and/or Data Science and hiring at a company where the bar for talent is set at the top of the market for the next generation of innovators and builders.

You’ve recruited at scale for research scientists, applied scientists, ML engineers, and data scientists. You understand the difference between a Machine Learning Engineer and an Applied Scientist. You’ve navigated nuanced leveling conversations, complex compensation structures, and competing offers from the best companies in the world — and you’ve won.

Now, bring that expertise to Salesforce, where Agentforce and Einstein AI are redefining what enterprise AI looks like. Your pipeline and your craft will directly shape the teams building the most impactful AI products in the world.

Agentforce & Einstein AI — You’ll be recruiting for the teams building the AI products deployed by the world’s largest enterprises, at a scale and data advantage no startup can match

Real Impact — This is not a support role. You will shape hiring strategy and directly influence how Salesforce’s AI org is built

World-Class Colleagues — Work alongside a high-performing recruiting team with deep expertise across the AI/ML talent landscape

Scope & Scale — Only a handful of companies in the world operate at Salesforce’s scale with this level of AI investment. The scope of what you’ll recruit for here is unmatched

Core Responsibilities & Scope

• Own full-cycle recruiting for Applied Scientist, Machine Learning Engineer, and/or Data Scientist roles across Salesforce’s AI and research organizations
• Partner deeply with senior engineering and research leaders to shape hiring strategy, define ideal candidate profiles, and influence how we compete for elite technical talent
• Build and maintain high-quality, research-grade talent pipelines — proactively mapping the market and engaging passive talent before requisitions open
• Lead complex offer negotiations, including sign-on and equity exception packages, with a clear understanding of market compensation benchmarks across FAANG and frontier AI companies
• Serve as a trusted advisor to hiring managers — pushing back, advising on tradeoffs, and bringing market intelligence that sharpens decision-making
• Collaborate with sourcing partners, recruiting coordinators, and peer advisors to run an efficient, high-touch candidate experience
• Contribute to team-level recruiting strategy, pipeline health reviews, and market talent intelligence initiatives

Minimum Requirements

• 5+ years of full-cycle technical recruiting experience, with a significant and demonstrated focus on Applied Science, Machine Learning, and/or Data Science roles
• Deep experience at a top-tier tech company — Meta, Google, or equivalent — where the talent bar is exceptionally high and the competition is fierce
• Proven ability to recruit across the full Applied Science and ML talent spectrum: ML Engineers, Data Scientists, Research Scientists, Applied Scientists, and MLOps Engineers
• Strong fluency in ML and AI concepts — enough to hold credible conversations with candidates and hiring managers about LLMs, deep learning, NLP, computer vision, and model development pipelines
• Track record of building proactive talent pipelines in highly contested, hard-to-fill research and applied ML talent pools
• Experience navigating complex compensation conversations, including base, equity (RSU), sign-on, and competing offer dynamics in the FAANG+ talent market
• Consultative, data-informed approach to recruiting — you bring market data, benchmarking intelligence, and candidate insights to every hiring manager interaction
• Strong communicator and relationship builder who earns trust quickly with both candidates and senior technical leaders

Preferred Qualifications

• Experience recruiting for frontier AI organizations, AI research labs, or applied AI product teams (e.g., FAIR, Google Brain/DeepMind, OpenAI)
• Familiarity with AI/ML academic pipelines and graduate recruiting from top research universities (MIT, Stanford, CMU, Berkeley, UW, etc.)
• Background working within large, matrixed organizations where recruiting requires influencing without authority