R&D Systems & Lab Operations Manager (Remote)
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Key skills for this role
About the Role
A client of Hired is seeking an R&D Systems & Lab Operations Manager on a contract basis to optimize and validate laboratory processes for AI model training. The role involves configuring ELNs and LIMS, designing workflows, and ensuring data quality across life sciences domains, with no prior AI experience required.
Key Skills for This Role
Responsibilities
- Develop, review, and refine rubrics to validate the accuracy, usability, and compliance of laboratory processes within ELNs and LIMS
- Design and optimize workflows for digital lab processes, ensuring integration with quality assurance documentation
- Translate domain specific lab protocols into structured, scalable procedures for automation and reinforcement learning environments
- Configure and maintain ELNs, LIMS, and related systems to support data management and process automation
- Conduct analytical reviews of lab data and process outputs to identify inefficiencies and recommend improvements
Requirements
- Experience with electronic lab notebooks (ELNs) and laboratory information management systems (LIMS)
- Demonstrated ability to design and refine workflows for digital lab operations
- Strong analytical skills and attention to detail
- Written and verbal communication proficiency
- Background in life sciences or related technical fields
Full Job Posting
Role Overview
- We are hiring for one of our clients, seeking a R&D Systems & Lab Operations Specialist to work on a Contractor basis.
- This role involves optimizing and validating laboratory processes for high impact AI model training, ensuring accuracy and usability of digital systems across life sciences domains such as healthcare, engineering, and finance.
- The position leverages domain expertise to refine operational workflows and contribute directly to the development of frontier AI models through structured data and process automation.
Key Responsibilities
- Develop, review, and refine rubrics to validate the accuracy, usability, and compliance of laboratory processes within electronic lab notebooks (ELNs) and laboratory information management systems (LIMS).
- Design and optimize workflows for digital lab processes, ensuring seamless integration with quality assurance documentation and cross functional collaboration.
- Translate domain specific lab protocols into structured, scalable procedures suitable for automation and reinforcement learning environments.
- Configure and maintain ELNs, LIMS, and related systems to support robust data management, traceability, and process automation in remote team settings.
- Conduct analytical reviews of lab data and process outputs to identify inefficiencies and recommend improvements aligned with digital transformation goals in life sciences.
Required Skills & Qualifications
- Experience with electronic lab notebooks (ELNs) and laboratory information management systems (LIMS), with a focus on system configuration and process optimization.
- Demonstrated ability to design and refine workflows for digital lab operations, including documentation and quality assurance integration.
- Strong analytical skills and attention to detail to evaluate lab protocols, translate requirements, and improve operational efficiency.
- Written and verbal communication proficiency to collaborate with global, remote teams and document complex lab processes clearly.
- Background in life sciences or related technical fields, with knowledge of lab data management and process automation methodologies.
- Familiarity with digital transformation initiatives in laboratory settings, including rubric development and review for performance validation.
More About the Opportunity
- This role offers a unique opportunity to contribute to the training and evaluation of next generation AI models by refining the systems that power human AI collaboration.
- Work with a global network of domain experts to shape how AI systems learn and perform across critical industries.
- The position provides exposure to cutting edge AI development workflows and the chance to influence scalable, high quality training data processes from a systems operations perspective.
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