Flux Computing · 1 month ago
Talent Coordinator
San Francisco
Full-time
Onsite
Mid Level
3+ years expFlux is pioneering a new class of AI accelerators called Optical Tensor Processing Units (OTPUs). They are seeking a Talent Acquisition Coordinator to support hiring during a critical growth period, focusing on providing a high touch candidate experience and facilitating the interview process in their San Francisco office.
Artificial Intelligence (AI)HardwareMachine LearningManufacturingOptical Communication
Responsibilities
Orchestrate end‑to‑end interview scheduling at pace—calendars, confirmations, and travel logistics included
Act as the communication hub, keeping candidates, recruiters, interviewers, and hiring managers aligned throughout the process
Welcome and host candidates during on‑site interview days
Maintain rigorous data quality in the Applicant Tracking System (ATS); keep records complete and current
Produce and share weekly pipeline and progress reports from the ATS
Tackle ad‑hoc initiatives that elevate Recruiting operations and impact
Proactively identity, plan and organise hiring events
Ensure candidates receive prompt reimbursement for their interview travel expenses
Onboarding and ad hoc office management support as required
Qualification
Required
3+ years of Talent Coordination experience, at least 1 year of which has been in-house at a fast-paced startup or high-growth tech company
Organised, responsive, and rigorous; you keep processes moving without dropping the ball
Passionate about candidate experience and helping build a hiring culture that scales and drives forward the company values
Preferred
Experience with employer branding, including facilitating bespoke hiring events
Benefits
Generous stock options in a rapidly growing AI company
Comprehensive healthcare insurance
25 days PTO policy plus bank holidays
Extra $24,000/year incentive for those living within 20 minutes
Company
Flux Computing
Flux Computing designs optical AI accelerators that use light-based processors for training and inference on large models.
51-200 employees
Funding
Current Stage
Growth StageCompany data provided by crunchbase