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Talent Acquisition Partner - Manufacturing at Bright Machines - ApplyBlast

Talent Acquisition Partner - Manufacturing

Bright Machines

3 months ago

3.4 on Glassdoor

Florence, Kentucky, United States

Onsite

Full Time

Senior

0 applicants

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About this role

Bright Machines is seeking a Talent Acquisition Partner to lead full-cycle recruiting for manufacturing and operations roles, including high-volume hourly hiring. The role involves partnering with Operations leaders to align workforce planning with production forecasts while building creative sourcing strategies and managing the candidate experience from intake to onboarding.

Responsibilities

Own full-cycle recruiting for manufacturing and operations roles from intake through offer acceptance
Lead high-volume hiring initiatives for Manufacturing Production workers supporting 24/7 operations
Build creative sourcing strategies utilizing job boards, referrals, and community organizations
Screen candidates, conduct interviews, and guide hiring managers through the selection process
Track recruiting metrics including time-to-fill, candidate conversion rates, and hiring funnel health

Skills

Qualifications

Bachelor's degree in Human Resources, Business, or related field

About Bright Machines

brightmachines.com

Headquarters

San Francisco, California, United States

Company Size

201-500 employees

Founded

2018

View Profile

Bright Machines is a manufacturing automation company that combines robotics, machine vision, and cloud-native software to deliver flexible, software-defined production systems. They build modular "microfactory" cells and intelligent assembly lines that automate repetitive manual tasks for electronics, medical devices, and consumer products using vision-guided robots, programmable tooling, and orchestration software. Their platform provides digital work instructions, real-time quality inspection, and production analytics to accelerate ramp-up, improve yields, and enable distributed, scalable manufacturing. Enterprises use Bright Machines to reduce labor dependency, shorten time-to-market, and make factory operations more programmable and data-driven.