Senior Technical Recruiter (AI/ML)

Quick Facts

• Role: Senior Technical Recruiter (AI/ML)
• Focus areas: Applied Science, Machine Learning Engineering, Data Science (AI research and applied AI teams)
• Type: Strategic, full-cycle recruiting for elite technical talent

Description

Own full-cycle, strategic recruiting for Applied Scientist, Machine Learning Engineer, and/or Data Scientist roles supporting Salesforce’s AI and research organizations. Build research-grade, proactive talent pipelines and proactively engage passive talent before requisitions open. Lead complex offer negotiations and partner with senior technical leaders to shape hiring strategy and candidate profiles.

Responsibilities

• Run end-to-end recruiting across Salesforce’s AI and research organizations for Applied Scientist, Machine Learning Engineer, and/or Data Scientist roles.
• Collaborate with senior engineering and research leaders to define ideal candidate profiles and hiring strategy.
• Develop and maintain high-quality, research-grade talent pipelines through ongoing market mapping and proactive outreach.
• Negotiate complex offers, including sign-on and equity exceptions, grounded in market compensation benchmarks.
• Advise hiring managers with tradeoff guidance and market intelligence.
• Partner with sourcing partners, recruiting coordinators, and peer advisors to deliver an efficient, high-touch candidate experience.
• Contribute to team recruiting strategy, pipeline health reviews, and market talent intelligence initiatives.

Requirements

• 5+ years of full-cycle technical recruiting experience with significant focus on Applied Science, Machine Learning, and/or Data Science.
• Deep experience at a top-tier tech company (e.g., Meta, Google, or equivalent) with a high talent bar.
• Proven ability to recruit across the Applied Science and ML talent spectrum: ML Engineers, Data Scientists, Research Scientists, Applied Scientists, and MLOps Engineers.
• Strong fluency in ML/AI concepts, including LLMs, deep learning, NLP, computer vision, and model development pipelines.
• Track record of building proactive talent pipelines for contested, hard-to-fill research and applied ML talent pools.
• Experience navigating complex compensation conversations (base, RSUs/equity, sign-on, and competing offers in the FAANG+ market).
• Consultative, data-informed recruiting approach using benchmarking intelligence and candidate insights.

Benefits

• Time off programs
• Medical, dental, vision
• Mental health support
• Paid parental leave
• Life and disability insurance
• 401(k)
• Employee stock purchasing program
• Typical base salary range: $117,400 – $177,600 annually (base salary only; may not include bonus/incentive, equity, or benefits)