Talent Recruiter – AI & ML Research

San Francisco, US

Symbolica

Evolving ML for the Evolving World

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About Us
Symbolica is an AI research lab pioneering the application of category theory to enable logical reasoning in machines.

We’re a well-resourced, nimble team of experts on a mission to bridge the gap between theoretical mathematics and cutting-edge technologies, creating symbolic reasoning models that think like humans – precise, logical, and interpretable. While others focus on scaling data-hungry neural networks, we’re building AI that understands the structures of thought, not just patterns in data.

Our approach combines rigorous research with fast-paced, results-driven execution. We’re reimagining the very foundations of intelligence while simultaneously developing product-focused machine learning models in a tight feedback loop, where research fuels application.

Founded in 2022, we’ve raised over $30M from leading Silicon Valley investors, including Khosla Ventures, General Catalyst, Abstract Ventures, and Day One Ventures, to push the boundaries of applying formal mathematics and logic to machine learning.

Our vision is to create AI systems that transform industries, empowering machines to solve humanity’s most complex challenges with precision and insight. Join us to redefine the future of AI by turning groundbreaking ideas into reality.

About The Role

You’ll join our team as the first Talent Recruiter in the US and take ownership of full-cycle hiring for some of the most specialized technical roles in AI — from ML Engineers and Research Scientists to ML Systems & Infra Engineers, and more. You’ll work side-by-side with the Talent Lead, C-level suite, and hiring managers to run highly targeted, deeply personalized recruiting processes aimed at attracting world-class talent who will help define the future of Symbolica. This is a rare opportunity to help shape a hiring engine in the US from scratch, directly influencing who joins our mission-critical founding teams, while collaborating closely with researchers, engineers, and leadership at every step.

📍 This is an onsite role based in our SF office.

Your Focus

  • Own full-cycle recruiting for highly specialized AI & technical roles (ML Engineers, Applied Researchers, ML Systems Engineers, etc.)
  • Proactively sourcing to ensure pipelines stay healthy and highly targeted
  • Drive a top-notch candidate experience from first outreach to offer stage
  • Partner closely with hiring managers and leadership to deeply understand role profiles and team needs
  • Run structured, efficient interview processes while maintaining a strong candidate experience throughout
  • Continuously refine outreach, screening, and assessment tactics to increase quality and conversion
  • Build long-term candidate relationships and nurture future hires even before roles open
  • Represent Symbolica as a brand ambassador in the US talent market

About You

  • 2+ years of experience running full-cycle recruiting for technical roles in AI / ML
  • Proven success hiring for highly specialized or hard-to-fill technical roles
  • Comfortable navigating fast-paced, ambiguous early-stage environments
  • Strong understanding of technical profiles and ability to evaluate candidate alignment at intake and screening stages
  • Deep attention to candidate experience and personalized engagement
  • Excellent written and verbal communication skills
  • Curious, resourceful, and proactive in driving pipelines forward with urgency

What We Offer

  • Full ownership and impact – directly influence all US-talent building the future of Symbolica
  • High-trust, low-bureaucracy environment focused on real execution
  • The opportunity to recruit for some of the hardest technical challenges in AI

Symbolica is an equal opportunities employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, gender, age, religion, disability, or sexual orientation.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Machine Learning Mathematics ML models Pipelines Research

Region: North America
Country: United States

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