Research Engineer

Title: Research Engineer, Data
Location: USA Remote
Compensation: Up to $400k + Equity
We're partnered with a well-funded AI research company focused on building next-generation multimodal models for media and interactive experiences. Their work spans cutting-edge generative systems and is increasingly moving toward real-time, interactive environments, pushing beyond static outputs into dynamic, AI-driven applications.
This is a high-impact, research-meets-engineering role focused on the data that powers advanced AI systems. You'll own how models learn, designing datasets, running experiments, and building data pipelines that directly shape model capabilities across a wide range of applications.
What You'll Do
Design multimodal, multitask datasets to unlock new model capabilities
Run controlled experiments to understand how data impacts model performance
Build and scale pipelines for synthetic data generation, filtering, and quality control
Define evaluation frameworks and benchmarks to measure real-world model improvement
Partner with cross-functional teams to translate product goals into data strategies
Requirements
4+ years of experience in machine learning, ideally with a data-centric focus
Experience working with large multimodal datasets and generative models
Strong intuition for how data quality and composition impact model behavior
Experience across the full ML lifecycle, from data to training to evaluation
Proficiency with ML frameworks such as PyTorch or JAX
Experience with distributed systems or compute tools (e.g., Ray, Kubernetes)
Strong interest in advancing next-generation AI systems
Nice to Have
Experience with synthetic data generation or data curation at scale
Background working on multimodal or video-based models
Exposure to evaluation and benchmarking for generative systems
If you're interested in shaping the data that defines what AI models can learn and do, this is a unique opportunity to work at the forefront of multimodal AI.

Work arrangement
Yes