Posted:11 hours ago|
Platform:
Remote
Contractual
Our client is a Palo Alto–based AI infrastructure and talent platform founded in 2018. It helps companies connect with remote software developers using AI-powered vetting and matching technology. Originally branded as the “Intelligent Talent Cloud,”enabled companies to “spin up their engineering dream team in the cloud” by sourcing and managing vetted global talent.
In recent years, they have evolved to support AI infrastructure and AGI workflows, offering services in model training, fine-tuning, and deployment—powered by their internal AI platform, ALAN, and backed by a vast talent network. They reported $300 million in revenue and reached profitability. Their growth is driven by demand for annotated training data from AI labs, including major clients like OpenAI, Google, Anthropic, and Meta.
We are seeking candidates with experience in any programming language or tech stacks to validate and ensure the quality of training data used in developing agentic AI systems. This role involves working with function-calling methods to create structured tasks, ensuring data workflows remain consistent, accurate, and aligned with cutting-edge AI requirements.
Validate large-scale training datasets and maintain strict quality standards.
Create, manipulate, and structure JSON tasks for function-calling workflows.
Work closely with AI researchers and teams to align datasets with agentic AI use cases.
Monitor data accuracy, consistency, and integrity across projects.
Contribute to documentation and best practices for dataset preparation and validation.
Strong proficiency in Python or JavaScript or Java or any other programming languages.
Solid understanding of SQL.
Expertise or Knowledge in handling JSON.
Exceptional attention to detail with a focus on data quality and consistency.
Interest in or exposure to agentic AI, LLMs, or NLP best practices.
Bonus: Prior experience with data annotation tools or prompt engineering for Agent AI.
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