Ultra builds practical, general-purpose robots focused on repetitive manipulation tasks.

Unlike traditional industrial automation that’s rigid and complex, our robots are zero integration—able to be installed in hours, not weeks—and are highly flexible, capable of quickly learning new tasks and delivering immediate ROI.

Founded by a team of three-time entrepreneurs with a decade of collaboration, Ultra moves fast and decisively. We already have robots in the field generating revenue and data, with plans to rapidly scale deployments this year.

Overview

We're seeking a Senior Machine Learning Engineer to join our NYC-based team (we are an in-person company), and own our ML infrastructure and data systems. As our robots scale, so does the volume of data we collect—we need someone who can build the systems to ingest, process, and serve petabytes of multimodal data for training our neural network policies. We are an early stage company moving very fast in a rapidly growing space, and welcome people from any background as long as you're excited to join our mission, drive immediate impact, and create a future where automation is accessible to all.

What You'll Do

• Own our data platform and scale it to ingest large amounts of video streams and make them available for training in real time
• Own our ML infrastructure stack end-to-end, including distributed training, experiment tracking, and cluster management
• Build out data management systems and high-performance data access layers on top of PB+ scale multimodal data
• Collaborate with the rest of our research team on designing and running experiments as we rapidly improve our policies’ capabilities
• Maintain high availability and reliability of critical infrastructure

Who You Are

• You have deep experience building and operating large-scale data systems (PB+ scale), ideally in domains like autonomous vehicles or robotics
• You're comfortable with real-time processing, streaming, and event-driven systems
• You have built deep learning training and inference systems at scale
• You thrive in a high-trust, high-autonomy environment. You don't need to be micromanaged on what the top priorities are at any given moment
• You're hungry for impact and personal growth, and like to have fun in the pursuit
• Deeply passionate about robotics and physical AI

Bonus Points

• Experience working on large-scale autonomous vehicles datasets or similar robotics domains
• Hands-on experience with distributed ML training at scale (1000+ GPU hours)
• Familiarity with video codecs, compression, and efficient video storage/retrieval systems
• Experience with reinforcement learning, imitation learning, or VLA model training pipelines
• Experience working with hardware systems in a production environment

About Ultra

Ultra builds AI-native industrial robots that actually work in the real world. Our systems automate mission-critical warehouse labor end-to-end, starting with e-commerce order packaging. We deploy fast, learn from real production data, and iterate aggressively. We already have multiple revenue-generating robots operating in U.S. warehouses, and are now scaling toward hundreds of deployments over the next couple years. Our goal is simple: build the most advanced, most productive industrial AI robots on the planet.

We’re building general-purpose robots that learn new tasks fast and deploy in hours, not weeks. Our stack combines real-time teleop, low-latency control, and neural network-based autonomy. We optimize end-to-end—from custom IK solvers and low-level drivers to vision-language-action models trained on production robot data. Stack: Python, C++, ROS2, PyTorch, simulation, real hardware. Problems: real-time control, robot learning, sim-to-real, scalable deployment.