Multimodal Data Architect for World Models

Goliath Partners Inc.; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Goliath Partners Inc. is seeking a Research Engineer (Datasets) to advance multimodal world models. You will own the data research lifecycle, from designing datasets and running experiments to building scalable synthetic data pipelines and evaluating model performance.

Join a fast-growing AI team that values curiosity, rigorous experiments, and responsible data practices. You’ll collaborate with research, product, and creative teams to translate goals into data strategy and drive meaningful

Qualifications

• 4+ years of experience in ML or AI.
• Experience with large multimodal datasets and generative models.
• Understanding of how data quality impacts model performance.
• Experience across the ML lifecycle: dataset creation, model training, evaluation, and experimentation.
• Proficiency with PyTorch, JAX, or similar frameworks.
• Experience with distributed computing tools such as Ray or Kubernetes.
• Curious, strong research instincts, and an experimental mindset.

Responsibilities

• Design multimodal datasets for foundational models.
• Run controlled experiments to study data composition effects on performance.
• Build and scale synthetic data generation, filtering, and QC pipelines.
• Develop evaluation frameworks and benchmarks to measure improvements.
• Partner with research, product, and creative teams to translate goals into data strategies.
• Iterate on datasets and training pipelines to improve world model capabilities.

Skills

4+ years of ML experience

Multimodal datasets experience

Data quality & composition

ML lifecycle expertise

PyTorch / JAX

Distributed computing (Ray / K8s)

Research mindset / curiosity

Tools

PyTorch

JAX

Ray

Kubernetes

Job description

Goliath Partners Inc. is seeking a Research Engineer (Datasets) to advance multimodal world models. You will own the data research lifecycle, from designing datasets and running experiments to building scalable synthetic data pipelines and evaluating model performance.

Join a fast-growing AI team that values curiosity, rigorous experiments, and responsible data practices. You’ll collaborate with research, product, and creative teams to translate goals into data strategy and drive meaningful