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As an early member of the Recruiting team at Reducto, you will play a pivotal role in shaping our growing engineering organization. You'll work closely with technical leaders and executives to drive full-cycle recruiting across Engineering, Machine Learning, and Infrastructure, from top-of-funnel strategy through offer negotiation and close. This is a high-impact role where you'll help build the recruiting foundation that scales with us for years to come.
Job Responsibility
Own full-cycle recruiting for technical roles, including sourcing, assessment, offer, negotiation, and close, with a focus on Engineering, ML, and Infrastructure
Partner directly with engineering leaders and executives to develop deep conviction on hiring needs, team objectives, and the profile of talent required to achieve them
Build and iterate on recruiting processes, interview loops, and top-of-funnel strategies that will scale as the team grows
Proactively source and engage passive talent through creative research, direct outreach, referrals, and community building
Guide candidates through the full journey, developing a clear understanding of their motivations and decision drivers to close effectively in a competitive market
Manage candidate pipelines with rigor and ensure an exceptional experience at every stage
Use data to drive decisions, tracking funnel metrics, conversion rates, and hiring pace to keep stakeholders informed and processes efficient
Requirements
4+ years of full-cycle recruiting experience, with at least 2 years focused on technical roles (software engineering, ML, or infrastructure)
Operate well in fast-changing, high-growth environments with a bias toward action
Collaborate effectively with technical leaders and can influence without authority
Take full ownership from sourcing strategy through close
Nice to have
Experience at an early-stage or hyper-growth startup
Familiar with the technical talent landscape and how top engineers evaluate opportunities
Sourced and closed candidates for highly competitive roles in AI, ML, or infrastructure
Care deeply about combining a great candidate experience with business impact