Research Engineer - Data Infrastructure/ML

third-dimension; San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Competitive salary & stock options

Pension / retirement plan

Health & wellness coverage

Flexible time off

Hybrid-first culture

Workspace support

Learning & development

Community & connection

Job summary

Third Dimension is building SuperSim, a scalable platform for AI-driven 3D data. We seek a Data Infrastructure / ML Engineer to design pipelines for 3D, video, image, and sensor data and to empower researchers to train, validate, and deploy models quickly.

You will work across cloud and containerized environments (Kubernetes, Ray, Dask) and collaborate with researchers to productionize ML models (PyTorch), develop data APIs, and improve data quality and lineage throughout the ML lifecycle.

Qualifications

• Strong programming background in Python.
• Proficiency with 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.).

Responsibilities

• 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).
• Collaborate with researchers to productionize ML models (PyTorch), from prototype to deployment.
• Develop tools and APIs that make data discoverable, reusable, and reproducible.
• Monitor and improve data quality, lineage, and performance across the ML lifecycle.

Skills

Python

Distributed data processing

Cloud infrastructure

Kubernetes

PyTorch

Ray

Dask

Spark

MLflow

DVC

Tools

PyTorch

Ray

Apache Spark

Flyte

Dask

Kubernetes

AWS

GCP

Azure

RLLib

Horovod

Job description

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.

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.

In this role, you will:

• 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 reproducible.
• Monitor and improve data quality, lineage, and performance across the ML lifecycle.

Preferred Qualifications & Skills

• 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.).

Nice to Haves

• Exposure to simulation, robotics, or autonomy testing pipelines.
• Experience with deep learning frameworks and ML workflows (PyTorch).
• Familiarity with 3D or robotics data formats (point clouds, meshes, radiance fields, LIDAR).
• Contributions to open-source ML/infra projects or publications in top-tier AI/ML/CV venues.
• Experience with frontend / UI work.

Location

• London, UK / Graz, Austria/ Bay Area: This is a priority for us, as we're trying to build a presence around our already existing teams in London, Graz or the Bay area. Hybrid (remote + in office days) preferred.
• Remote: If hybrid is not an option, but you're amazing, we're open to having you work out your home location.

Benefits

• Competitive salary & stock options - Everyone is an owner and shares in our success.
• Pension / retirement plan - Company contributions to support your long-term financial wellbeing.
• Health & wellness - Comprehensive health, dental, and vision insurance (with regional equivalents for employees outside the UK).
• Flexible time off - Generous holiday allowance plus local public holidays.
• Hybrid-first culture - State-of-the-art London workspace with the flexibility to work remotely.
• Workspace support - Latest hardware and home office equipment to set you up for success.
• Learning & development - Budget and time for conferences, courses, and workshops to keep you at the frontier of ML and 3D AI.
• Community & connection - Team offsites, events, and opportunities to connect with global colleagues.