Machine Learning Engineer @ UnitX
Unitxlabs
San Francisco, CAOn-siteFull-time$140k – $220k / year
About this role
Machine Learning Engineer @ UnitX
- Back to UnitX’s Job Listings
Machine Learning Engineer
Location
HQ
Employment Type
Full time
Location Type
On-site
Department
Software
Compensation
- $170K – $200K • Offers Equity
Job Title:
Machine Learning Engineer
About Us:
UnitX builds the world's leading physical AI systems to automate repetitive visual tasks in factories. UnitX is a fast-moving startup with a team from Stanford, MIT, Google, and beyond. Since inception, UnitX has deployed 1,000+ mission-critical systems across 190+ of the world's leading manufacturers' production lines. Every year, $15B worth of products go through UnitX's AI inspection system to ensure quality.
Join us for the rare opportunity to work on computer-vision-driven products that go beyond the state of the art and that improve global manufacturing efficiency.
What You'll Do:
Develop & Optimize Machine Learning Models: Design, train, and optimize deep learning models for defect detection and segmentation using high-resolution images and 3D sensor inputs. You will implement advanced computer vision techniques (including Stable Diffusion, Segment Anything Model (SAM), and transformer-based architectures) to ensure pixel-level precision and real-time inference.
Build Automated Pipelines: Develop and maintain automated pipelines for data preprocessing, augmentation, and model training to continuously optimize deployed solutions.
Deploy & Maintain Production-Ready Software: Develop scalable ML pipelines for deployment on both edge devices and cloud-based systems. You will optimize model inference for real-time decision-making, ensuring processing times remain under 20 milliseconds.
Collaborate Cross-Functionally: Work closely with software engineers, robotics specialists, and hardware teams to seamlessly integrate ML solutions into fully automated industrial workflows.
Monitor & Ensure Reliability: Implement automated monitoring and alerting systems to track mode
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