The Role
As a Senior Machine Learning Engineer, you will own ML infrastructure and data systems, scaling them for large volumes of video data and supporting deep learning training and experimentation.
Summary Generated by Built In
About Ultra
What You'll Do
Who You Are
Bonus Points
Ultra builds industrial AI robots that are working in the real world today. Our robots 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.
OverviewWe'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.
- 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
- 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
- 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
Expected Compensation
$175,000 - $250,000/annual salary + equity + benefits
This compensation range may be inclusive of several career levels at Ultra and will be narrowed during the interview process based on the candidate’s experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description.
Equal Employment Opportunity Statement
We are an Equal Opportunity Employer. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to creating a diverse and inclusive environment and encourage applicants from all backgrounds to apply.
Top Skills
Data Engineering
Deep Learning
Distributed Training
Event-Driven Systems
Machine Learning
Real-Time Processing
Video Codecs
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The Company
What We Do
Ultra builds intelligent warehouse robots that are being deployed in warehouses today. Our purpose-built robots are practically designed for end-to-end task automation, starting with ecommerce order packaging.
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