Spaitial Ltd.
SpAItial is pioneering the development of a frontier 3D foundation model, pushing the boundaries of AI, computer vision, and spatial computing. Our mission is to redefine how industries, from robotics and AR/VR to gaming and movies, generate and interact with 3D content. We're seeking a Data Engineer to build the pipelines and infrastructure that fuel our large-scale model training. As the first engineer focused on data, you'll shape the backbone of how we handle terabytes of multimodal training data (images, video, and 3D). This role is ideal for someone who thrives at the intersection of data systems and machine learning-designing reliable, scalable, and efficient ways to get high-quality data into cutting edge training runs. Responsibilities Architect and manage data infrastructure for large-scale ML training datasets (e.g., Apache, Iceberg, Parquet, Spark). Build and operate ingestion pipelines for multimodal data (e.g., images, videos, 3D). Design data loaders, caching, and serving strategies optimized for ML training. Partner closely with ML researchers to ensure infrastructure scales with training demands. Uphold code quality and best practices in testing, CI/CD, and reproducibility. Key Qualifications 3+ years professional software/data engineering experience with production systems. Proven experience in large-scale data processing for ML training (not just analytics/BI). Hands on with distributed data frameworks (e.g., Spark, Beam, Cloud SQL, AirFlow) and modern data formats (Parquet, Iceberg). Proficiency in cloud platforms (AWS, GCP, or Azure). Strong Python development skills, including testing and code quality. Experience building and maintaining CI/CD pipelines. Preferred Qualifications Familiarity with ML frameworks (e.g., PyTorch, TensorFlow). Experience preparing multimodal datasets (images, video, 3D) for ML pipelines. At SpAItial, we are committed to creating a diverse and inclusive workplace. We welcome applications from people of all backgrounds, experiences, and perspectives. We are an equal opportunity employer and ensure all candidates are treated fairly throughout the recruitment process.
SpAItial is pioneering the development of a frontier 3D foundation model, pushing the boundaries of AI, computer vision, and spatial computing. Our mission is to redefine how industries, from robotics and AR/VR to gaming and movies, generate and interact with 3D content. We're seeking a Data Engineer to build the pipelines and infrastructure that fuel our large-scale model training. As the first engineer focused on data, you'll shape the backbone of how we handle terabytes of multimodal training data (images, video, and 3D). This role is ideal for someone who thrives at the intersection of data systems and machine learning-designing reliable, scalable, and efficient ways to get high-quality data into cutting edge training runs. Responsibilities Architect and manage data infrastructure for large-scale ML training datasets (e.g., Apache, Iceberg, Parquet, Spark). Build and operate ingestion pipelines for multimodal data (e.g., images, videos, 3D). Design data loaders, caching, and serving strategies optimized for ML training. Partner closely with ML researchers to ensure infrastructure scales with training demands. Uphold code quality and best practices in testing, CI/CD, and reproducibility. Key Qualifications 3+ years professional software/data engineering experience with production systems. Proven experience in large-scale data processing for ML training (not just analytics/BI). Hands on with distributed data frameworks (e.g., Spark, Beam, Cloud SQL, AirFlow) and modern data formats (Parquet, Iceberg). Proficiency in cloud platforms (AWS, GCP, or Azure). Strong Python development skills, including testing and code quality. Experience building and maintaining CI/CD pipelines. Preferred Qualifications Familiarity with ML frameworks (e.g., PyTorch, TensorFlow). Experience preparing multimodal datasets (images, video, 3D) for ML pipelines. At SpAItial, we are committed to creating a diverse and inclusive workplace. We welcome applications from people of all backgrounds, experiences, and perspectives. We are an equal opportunity employer and ensure all candidates are treated fairly throughout the recruitment process.