Startups · AI

Research Engineer - Data Infrastructure/ML

Thirddimension · United States - Remote · Remote

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About Thirddimension

Third Dimension is building spatial generation to power tomorrow's embodied AI and enable new frontiers of creativity in gaming and entertainment. Backed by Felicis.

About the role

We’re looking for a Data Infrastructure / ML Engineer to build the backbone of our 3D AI systems. You’ll design scalable pipelines for 3D, video, image, and other sensor data (e.g., LIDAR) and develop the ML workflows that power SuperSim. Your work will enable our researchers to train, validate, and deploy models faster - ultimately shaping how robots and autonomous systems are tested in the real world.

What they're looking for

  • Strong programming background in Python
  • Proficiency in distributed data-processing technologies (e.g., Ray, Apache Spark, Flyte, Dask)
  • Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), Kubernetes, and distributed training frameworks (Ray, RLLib, PyTorch DDP, or Horovod)
  • Knowledge of dataset versioning, experiment tracking, and reproducibility tools (DVC, MLflow, etc.)
More about this role

Third Dimension is building SuperSim, a new kind of simulator which can enable fast, cost-effective and photorealistic 3D simulations directly from source data using AI. We are working with customers across multiple industries, including autonomous vehicles, drones, robots in industrial and manufacturing environments, and more.

We’re looking for a Data Infrastructure / ML Engineer to build the backbone of our 3D AI systems. You’ll design scalable pipelines for 3D, video, image, and other sensor data (e.g., LIDAR) and develop the ML workflows that power SuperSim. Your work will enable our researchers to train, validate, and deploy models faster - ultimately shaping how robots and autonomous systems are tested in the real world.

  • Build and maintain high-performance data pipelines to ingest, transform, and version multi-modal datasets (3D, video, sensor).
  • Design and optimize distributed training and data-processing infrastructure - across cloud and containerized environments (Kubernetes, Ray, Dask, EKS, Buildkite).
  • Collaborate with researchers to productionize ML models (PyTorch), from prototype to deployment.
  • Develop tools and APIs that make data discoverable, reusable, and...

Read the full posting on Thirddimension's site ↗

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