develop and execute data strategies for coding capabilities, cybersecurity evaluations, and agentic AI research
partner with research leaders to translate technical requirements into operational frameworks
build data collection and evaluation systems through internal tools, vendor partnerships, and new approaches
identify, evaluate, and manage specialized contractors and vendors for technical data collection
implement quality control processes to ensure data meets training requirements
manage multiple complex projects simultaneously, balancing technical needs with delivery timelines
track metrics and communicate progress to stakeholders

3+ years in technical operations, product management, or entrepreneurial experience building from zero to scale
strong technical foundations
proficiency in Python and understanding of ML workflows and evaluation frameworks
strong communication skills and can effectively engage with both technical and non-technical stakeholders, both internal and external parties
familiar with how LLMs work and could describe how models like Claude are trained
highly organized and can manage multiple parallel workstreams effectively
high threshold for navigating ambiguity and can balance setting strategic priorities with rapid, high-quality execution
thrive in fast-paced research environments with shifting priorities and novel technical challenges
passionate about AI safety and understand the critical importance of high-quality data in building beneficial AI systems

Data Operations Manager

Key skills