Data Infrastructure Engineer

We’re looking for a Data Infrastructure Engineer to own and build the data systems that power Verne’s robots in the real world. This is a hands-on founding engineer role with true ownership and freedom - your work will directly impact robots performing customer-critical tasks every day.

You will architect and deploy data pipelines on both AWS and edge devices, manage large-scale multi-modal datasets (images, video, time-series, text, etc.), and build the tooling that connects real-world robot data to training and evaluation workflows. You’ll work across the full robotics software stack, from ingesting sensor data and telemetry, to enabling large-scale policy learning pipelines that drive production robots.

Beyond writing great code, you’ll help drive technical decisions, lead cross-functional efforts, and bridge robotics, machine learning, and product requirements into scalable, reliable systems.

What You’ll Do

• Build and own our data backbone on AWS: Design and run cloud + edge pipelines using services like IoT Core, S3, ECR, Batch, ECS/EKS, and Step Functions. Your work keeps robot data flowing reliably and cost-efficiently from the field into the lab.
• Develop on-device data systems: Build robust, fault-tolerant data capture on edge PCs using MCAP/Protobuf, with clean schema contracts, buffering, and resumable uploads to the cloud.
• Wrangle massive multimodal datasets: Organize and version millions of images, videos, time-series (robot state, force/torque), and annotations. Enforce metadata, retention, and access patterns that scale.
• Build MLOps and DataOps pipelines: Automate data validation, labeling, augmentation, and model training/evaluation using containerized jobs and orchestrators like Batch, Step Functions, Airflow, or Prefect.
• Ensure data quality and health: Create ingestion checks, schema validation, deduping, drift detection, and real-time alerting around data freshness and completeness.
• Build internal tools that unblock others: Develop UIs/CLIs for browsing data, launching jobs, tracking experiments, and debugging robots in the field. Integrate with tools like Foxglove.
• Work across teams: Partner with hardware, ML, and product to turn raw field data into smarter robots and real customer value-fast.

• B.S., M.S., Ph.D. in computer science or related fields.
• Strong programming skills in Python (you write clean, efficient, production-ready code)
• Strong experience in AWS
• Systems engineering skills (networking, concurrency, performance)
• At least 2 years of full-time work experience for candidates with a B.S. in related fields. 1 year of experience for M.S. or Ph.D. candidates.

Verne is building physical AI to make physical work as scalable as software and bring general-purpose robots to every business. We develop robots, foundation models, and the tools that turn them into reliable industrial deployments.

Our open-weight world action model, Verne V0.5, brings together video and action learning. Alongside it, we build data and training systems, a fine-tuning platform, and inference and control software. Our work is grounded in real deployments: learning new tasks efficiently, adapting to different environments, and operating reliably in production., At Verne, you won’t just be writing code - you’ll be shaping the future of physical AI. Our mission is simple but ambitious: free humans from tedious manual work by deploying low-cost robotic automation at scale and democratizing bimanual robot manipulators for the world.

You’ll build systems that run on real robots, in real customer environments, driving immediate and tangible impact. You’ll join a small, world-class team where your ideas matter, your ownership is real, and your growth is accelerated. If you’re excited by hard problems, fast execution, and the chance to industrialize AI in the physical world, this is the team to be on.