Research Engineer

About the role

You will take ownership of the data strategy behind large scale multimodal models, influencing both research direction and real world product capability. Design and build large scale multimodal datasets across image and video domains. Run structured experiments to understand how dataset composition impacts model performance. Develop and maintain pipelines for synthetic data generation, curation, and quality control. Define robust evaluation frameworks and benchmarks aligned to real use cases. Collaborate with research, product, and creative teams to translate goals into data strategies. Contribute to model training workflows, including pre training and fine tuning.

Responsibilities

• Strong commercial experience working with large scale machine learning or foundation models
• Hands on expertise with multimodal data, particularly image or video based systems
• Deep understanding of dataset design, curation, and evaluation in model performance
• Experience working across the full ML lifecycle including training, experimentation, and analysis
• Proficiency in frameworks such as PyTorch or JAX and distributed compute tools
• Evidence of research contribution, open source work, or strong technical projects
• A curiosity driven mindset with a genuine interest in advancing AI capabilities

Requirements

• Highly competitive compensation with equity participation
• Full remote working with a globally distributed team
• Significant ownership and influence over core model capabilities
• Opportunity to work on frontier AI challenges with real world impact
• A fast paced, low ego environment focused on innovation and learning

Qualifications

• Strong commercial experience working with large scale machine learning or foundation models
• Hands on expertise with multimodal data, particularly image or video based systems
• Deep understanding of dataset design, curation, and evaluation in model performance
• Experience working across the full ML lifecycle including training, experimentation, and analysis
• Proficiency in frameworks such as PyTorch or JAX and distributed compute tools
• Evidence of research contribution, open source work, or strong technical projects

Skills

• Strong commercial experience working with large scale machine learning or foundation models
• Hands on expertise with multimodal data, particularly image or video based systems
• Deep understanding of dataset design, curation, and evaluation in model performance
• Experience working across the full ML lifecycle including training, experimentation, and analysis
• Proficiency in frameworks such as PyTorch or JAX and distributed compute tools
• Evidence of research contribution, open source work, or strong technical projects

Benefits

• Highly competitive compensation with equity participation
• Full remote working with a globally distributed team
• Significant ownership and influence over core model capabilities
• Opportunity to work on frontier AI challenges with real world impact
• A fast paced, low ego environment focused on innovation and learning

Pay

• $400k + Equity

Schedule

• Remote