Data Engineer / ML Ops

About the role

VC-backed multimodal AI startup is hiring a Data Engineer / ML Ops to build the data foundation for real-time video and audio AI models. This is a fully remote, foundational role with direct founder collaboration.

Responsibilities

• Own the end-to-end data strategy for multimodal datasets
• Architect the data foundation for authentic, real-time AI humans
• Source, curate, and structure large-scale multimodal datasets for proprietary model training
• Build massive pipelines for video, audio, and text data
• Power proprietary models at the frontier of AI research
• Work directly with founders on complex infrastructure problems
• Architect and optimize high-performance data pipelines
• Build automated labeling workflows to scale ML production
• Define engineering best practices
• Proactively build the data foundation for next-generation conversational AI
• Act as the first dedicated data hire

Requirements

• Expert proficiency in Python
• Expert proficiency in SQL
• Experience building large-scale data processing systems in a production environment
• Proven experience working with LLMs
• Experience managing complex multimodal data challenges like video and audio
• Startup builder mentality
• Extreme ownership
• Ability to define standards in new problem spaces

Additional Skills

• Large-scale data processing systems, production environments
• Video, audio, text data pipelines
• Automated labeling workflows
• ML production
• Engineering best practices
• Conversational AI

Company: VC-backed multimodal AI startup
Location: Fully remote
Experience: 3-5 years
Pay: $25.3K–38.6K/yr
Schedule: Full-time