Lead Technical Recruiter (Quant Engineering)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Own end-to-end recruiting for Quantitative Engineering and Algorithmic Trading roles, partnering with engineering leaders to meet ambitious hiring goals. Build sourcing strategies to attract world-class quant and machine learning talent, leveraging niche channels and conferences. Run intake, interview kick-off, and technical debriefs to maintain a data-driven hiring bar, while delivering white-glove candidate experience and weekly analytics to hiring managers and senior leadership.

Location: New York, London

Workplace: Hybrid

Employment Type: Full time

Job Function: People, HR & Talent

Seniority: Mid level

Key Responsibilities

•Own specialized recruiting from sourcing through complex offer negotiations for Quantitative Engineering and Algorithmic Trading roles.
•Develop recruiting strategies and sourcing approaches to meet aggressive hiring goals in partnership with Engineering Leads.
•Plan and execute sourcing using niche channels such as Kaggle, GitHub, ArXiv, Codeforces, NeurIPS, and ICML.
•Run intake, interview team kick-off, and technical debrief processes to support a data-driven hiring bar.
•Provide white-glove candidate experience and deliver weekly performance analytics and progress reports to hiring managers and senior leadership.

Pay and Benefits

Perks:Learning BudgetHealth InsuranceRetirementParental LeaveMobile StipendWellness StipendPaid LeaveMeal AllowanceEquityAnnual Bonus

Key Requirements

•7+ years of recruiting experience, including 3+ years focused on Quantitative Engineering, High-Frequency Trading (HFT), or Machine Learning talent.
•Strong sourcing skills with a track record of converting passive, highly-compensated talent into hires.
•In-depth understanding of the quantitative tech stack, including C++, Python (NumPy/Pandas), Rust, low-latency systems, and distributed computing.
•Experience sourcing through niche channels (e.g., math Olympiads, research labs, and diversity-in-STEM academic events).
•Proficiency using Greenhouse (ATS), LinkedIn Recruiter, specialized sourcing tools (Entelo, SeekOut), and technical repositories like GitHub.

Experience:7+ yearsFinTechHigh-frequency tradingMachine learningAlgorithmic trading

Skills:CommunicationOrganizationStakeholder management

Languages:English

Tech Stack:C++PythonNumPyPandasRustGreenhouseLinkedIn RecruiterEnteloSeekOutGitHubDistributed Computing

Company Brief

Ripple

Website

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Ripple

4 months ago

Lead Technical Recruiter (Quant Engineering)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: New York, London

Workplace: Hybrid

Employment Type: Full time

Job Function: People, HR & Talent

Seniority: Mid level

Key Responsibilities

•Own specialized recruiting from sourcing through complex offer negotiations for Quantitative Engineering and Algorithmic Trading roles.
•Develop recruiting strategies and sourcing approaches to meet aggressive hiring goals in partnership with Engineering Leads.
•Plan and execute sourcing using niche channels such as Kaggle, GitHub, ArXiv, Codeforces, NeurIPS, and ICML.
•Run intake, interview team kick-off, and technical debrief processes to support a data-driven hiring bar.
•Provide white-glove candidate experience and deliver weekly performance analytics and progress reports to hiring managers and senior leadership.

Pay and Benefits

Perks:Learning BudgetHealth InsuranceRetirementParental LeaveMobile StipendWellness StipendPaid LeaveMeal AllowanceEquityAnnual Bonus

Key Requirements

•7+ years of recruiting experience, including 3+ years focused on Quantitative Engineering, High-Frequency Trading (HFT), or Machine Learning talent.
•Strong sourcing skills with a track record of converting passive, highly-compensated talent into hires.
•In-depth understanding of the quantitative tech stack, including C++, Python (NumPy/Pandas), Rust, low-latency systems, and distributed computing.
•Experience sourcing through niche channels (e.g., math Olympiads, research labs, and diversity-in-STEM academic events).
•Proficiency using Greenhouse (ATS), LinkedIn Recruiter, specialized sourcing tools (Entelo, SeekOut), and technical repositories like GitHub.

Experience:7+ yearsFinTechHigh-frequency tradingMachine learningAlgorithmic trading

Skills:CommunicationOrganizationStakeholder management

Languages:English

Tech Stack:C++PythonNumPyPandasRustGreenhouseLinkedIn RecruiterEnteloSeekOutGitHubDistributed Computing

Company Brief

Ripple

Website