Technical Sourcer

Ovii's Interpretation of the Role

The Technical Sourcer will drive growth at Cartesia by designing and executing sourcing strategies for high‑impact AI/ML engineering roles, managing pipelines, and delivering a premium candidate experience.

Role Snapshot

• Technical talent sourcing
• Engineering hiring focus
• Strategic talent mapping
• Pipeline generation
• Personalized candidate outreach
• Cross‑functional partnership

Must-Have Requirements

• Technical sourcing
• Boolean search
• Talent mapping
• ATS management
• Written & verbal communication
• technical sourcing
• engineering hiring

Nice-to-Have Signals

• Machine learning / deep learning / NLP knowledge
• Academic conference sourcing experience
• Open‑source community sourcing experience
• AI/ML domain sourcing
• AI
• Machine Learning
• Deep Learning
• NLP

Work Setup

• Location: San Francisco, United States
• Work mode: ONSITE
• Employment type: Full-Time

Eligibility Gates

• Work authorization: must be eligible to work in the United States
• Visa sponsorship: yes

Not Specified in JD

• Salary range
• Remote eligibility
• Exact visa sponsorship guarantee
• Education requirement

What You'll Likely Work On

• Create and run innovative sourcing plans for research, platform, and product engineering positions.
• Leverage academic conferences, research publications, GitHub, Hugging Face, and professional networks to locate top AI/ML talent.
• Build and sustain a robust pipeline of passive candidates for current and future hiring needs.
• Write compelling, personalized outreach messages that resonate with highly technical candidates.
• Serve as the primary point of contact, ensuring a seamless and positive candidate journey.
• Collaborate closely with recruiting and hiring managers to refine role requirements and calibrate search tactics.

Good Fit If You Have

• Curiosity about the AI/ML landscape and emerging research.
• Meticulous attention to detail in pipeline and data management.
• Experience sourcing for specialized technical roles such as ML, NLP, or large‑scale systems.