Multimodal AI Data Research Engineer

Harnham; California; Vor Ort; USD 150.000 - 230.000; Vollzeit

Zusammenfassung

Harnham in California is seeking a data-focused ML engineer to own data powering next-generation AI systems. You will design multimodal datasets, run controlled experiments, and build scalable data pipelines for synthetic data generation and quality control.

You will define evaluation benchmarks and collaborate with cross-functional teams to translate product goals into data strategies, leveraging PyTorch or JAX and distributed compute tools.

Qualifikationen

• 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.

Aufgaben

• 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.

Kenntnisse

Multimodal datasets

Data-centric ML

PyTorch

JAX

Ray

Kubernetes

Tools

PyTorch

JAX

Ray

Kubernetes

Jobbeschreibung

Harnham in California is seeking a data-focused ML engineer to own data powering next-generation AI systems. You will design multimodal datasets, run controlled experiments, and build scalable data pipelines for synthetic data generation and quality control.

You will define evaluation benchmarks and collaborate with cross-functional teams to translate product goals into data strategies, leveraging PyTorch or JAX and distributed compute tools.