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AI Summary
About Us
Our mission is to raise AGI with the richness of human intelligence — curious, witty, imaginative, and full of unexpected brilliance.
Surge was founded by engineers and researchers who dreamed of building the next generation AI. We're building a platform that powers the most powerful models in the world in partnership with companies like Anthropic, Google, Microsoft, and Meta.
At Surge, we believe the path to AGI isn't just about scaling compute—it's about embracing the unlimited ceiling of human intelligence and creativity in the data that shapes these systems. Our platform combines elite human expertise with cutting-edge tools for scalable oversight, from building rich RL environments to conducting rigorous evaluations that go beyond benchmarks. We've run a profitable business from day one without raising venture funding.
The Role
As a Strategic Projects Lead at Surge, you will ensure that our data collection, processing, and management systems operate efficiently and scale with our growing needs. You will work closely with engineering, product, and operations teams to ensure that our data pipelines and processes are optimized for both speed and quality. This is a great opportunity for someone who thrives in dynamic environments and is passionate about making data flow seamlessly through complex systems.
What You'll Do
Manage the end-to-end data operations process, ensuring data is collected, processed, and delivered efficiently and accurately.
Collaborate with product and engineering teams to refine data pipelines and improve data flow across systems.
Establish and monitor key data quality metrics, ensuring the consistency and reliability of data used for training AI models.
Identify operational inefficiencies in data workflows and implement solutions to improve speed and quality.
Provide actionable insights from data analysis, supporting teams in decision-making and product development.
What We're Looking for
Strong technical skills, with experience in managing data pipelines and ensuring data quality (experience with SQL, Python, or similar tools preferred).
Excellent problem-solving skills and a data-driven approach to improving processes and systems.
Strong collaboration skills with the ability to work cross-functionally and communicate complex data issues to non-technical stakeholders.
Interest in AI/ML systems is a plus, but not required.
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