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: 1 hour agoStatus: Live

Job Summary

Own end-to-end recruiting for Quantitative Engineering and Algorithmic Trading roles, partnering with hiring managers to define talent needs and drive data-driven hiring. Build innovative sourcing strategies using niche channels and deliver a white-glove candidate experience for rigorous technical assessments. Collaborate with engineering leads on aggressive hiring goals, manage technical debrief workflows, and provide weekly performance analytics and progress reporting to senior leadership.

Location: New York, London

Workplace: Hybrid

Employment Type: Full time

Job Function: People, HR & Talent

Key Responsibilities

•Own specialized recruiting from sourcing through complex offer negotiations for Quantitative Engineering and Algorithmic Trading roles.
•Develop strategies to meet aggressive hiring goals in partnership with engineering leads and align technical priorities.
•Create out-of-the-box sourcing plans targeting elite talent via channels such as Kaggle, GitHub, ArXiv, Codeforces, and quant finance conferences.
•Run intake, interview team kick-offs, and technical debrief processes to maintain a data-driven hiring bar.
•Provide weekly performance analytics and progress updates to hiring managers and senior leadership.

Pay and Benefits

Salary: USD 144,000 - 180,000 annually

Perks:Learning BudgetHealth InsuranceRetirementParental LeaveMobile Phone

Key Requirements

•7+ years recruiting experience, including 3+ years focused on Quantitative Engineering, High-Frequency Trading (HFT), or Machine Learning talent.
•Experience blending agency specialized search and in-house startup recruiting to handle both high-volume and high-touch hiring.
•Strong sourcing ability, including converting passive, highly compensated talent into hires.
•In-depth knowledge of quant tech stack topics, including C++, Python (NumPy/Pandas), Rust, low-latency systems, and distributed computing.
•Experience with recruiting tools and channels such as Greenhouse (ATS), LinkedIn Recruiter, Entelo/SeekOut, and technical repositories like GitHub.

Experience:7+ yearsFintechHigh-frequency tradingMachine learningQuantitative finance

Skills:Organizational precisionCommunicationStrategic thinkingCollaborationSelf-starter mindset

Languages:English

Tech Stack:C++PythonNumPyPandasRustLow-Latency systemsDistributed ComputingGreenhouseLinkedIn RecruiterEnteloSeekOutGitHubKaggleArXivCodeforces

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: 1 hour agoStatus: Live

Job Summary

Location: New York, London

Workplace: Hybrid

Employment Type: Full time

Job Function: People, HR & Talent

Key Responsibilities

•Own specialized recruiting from sourcing through complex offer negotiations for Quantitative Engineering and Algorithmic Trading roles.
•Develop strategies to meet aggressive hiring goals in partnership with engineering leads and align technical priorities.
•Create out-of-the-box sourcing plans targeting elite talent via channels such as Kaggle, GitHub, ArXiv, Codeforces, and quant finance conferences.
•Run intake, interview team kick-offs, and technical debrief processes to maintain a data-driven hiring bar.
•Provide weekly performance analytics and progress updates to hiring managers and senior leadership.

Pay and Benefits

Salary: USD 144,000 - 180,000 annually

Perks:Learning BudgetHealth InsuranceRetirementParental LeaveMobile Phone

Key Requirements

•7+ years recruiting experience, including 3+ years focused on Quantitative Engineering, High-Frequency Trading (HFT), or Machine Learning talent.
•Experience blending agency specialized search and in-house startup recruiting to handle both high-volume and high-touch hiring.
•Strong sourcing ability, including converting passive, highly compensated talent into hires.
•In-depth knowledge of quant tech stack topics, including C++, Python (NumPy/Pandas), Rust, low-latency systems, and distributed computing.
•Experience with recruiting tools and channels such as Greenhouse (ATS), LinkedIn Recruiter, Entelo/SeekOut, and technical repositories like GitHub.

Experience:7+ yearsFintechHigh-frequency tradingMachine learningQuantitative finance

Skills:Organizational precisionCommunicationStrategic thinkingCollaborationSelf-starter mindset

Languages:English

Tech Stack:C++PythonNumPyPandasRustLow-Latency systemsDistributed ComputingGreenhouseLinkedIn RecruiterEnteloSeekOutGitHubKaggleArXivCodeforces

Company Brief

Ripple

Website